Download Hi-Res ImageDownload to MS-PowerPointCite This:ACS Cent. Sci. 2020, 6, 11, 1890-1900

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Daniele Ongari
Daniele Ongari
Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland
More by Daniele Ongari
http://orcid.org/0000-0001-6197-2901
,
Leopold Talirz
Leopold Talirz
Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland
Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
More by Leopold Talirz
http://orcid.org/0000-0002-1524-5903
, and
Berend Smit*
Berend Smit
Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland
*E-mail: [email protected]
More by Berend Smit
http://orcid.org/0000-0003-4653-8562

Cite this: ACS Cent. Sci. 2020, 6, 11, 1890–1900

Publication Date (Web):October 2, 2020

https://doi.org/10.1021/acscentsci.0c00988

Request reuse permissions

Article Views

6490

Altmetric

Citations

LEARN ABOUT THESE METRICS

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.

PDF (5 MB)

Get e-Alerts

SUBJECTS:

Get e-Alerts

Abstract

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials’ performances. We discuss the impact that reproducibility and automation of the modeling protocols have on the field of gas adsorption in nanoporous crystals. We envision a platform that combines these tools and enables effective matching between promising materials and industrial applications.

Synopsis

We identify the opportunity for a computational platform for matching nanoporous materials and gas-related applications, motivating the development of automated and reproducible computational workflows.

Introduction

ARTICLE SECTIONS

Jump To

In this Outlook, we are indulging in a luxury problem: too many materials with too many possible applications. In the field of nanoporous materials, more than 100 000 metal–organic frameworks (MOFs) have been reported (Figure 1), with large design spaces also guaranteed for covalent organic frameworks (COFs), zeolites, porous organic cages, etc. At the same time, the range of applications of these materials is expanding from gas separation (1) and gas storage (2) to fields such as catalysis (3,4) and sensing. (5,6) A new material is often designed and tested for one specific application; testing it for a wide range of applications may exceed the expertise, time resources, and/or infrastructure of the research group synthesizing the material. Conversely, research groups focused on the application side can no longer afford to test all materials of possible interest.

Figure 1. (a) Papers mentioning “Zeolite”, “Metal Organic Framework”, and “Covalent Organic Framework” in the title or the abstract, as parsed from Scopus in July 2020. (7) The right column collects histograms for the deposition of materials in publicly available databases. (b) Zeolite code types by year of assignment, from the database of the International Zeolite Association (IZA). (8) (c) MOF-subset of the Cambridge Structural Database (CSD, May 20 update) by year of publication (orange). (9) MOFs in the CoRE-2019 “All solvent Removed” (ASR) subset (purple) are selected from the CSD release of November 2017 with criteria such as three-dimensionality of the framework and permeability to small molecules. (10) (d) COFs in the CURATED-COFs database (June 20 update), by year of publication. (11,12)

Let us illustrate this point with a few examples. Al-PMOF was first synthesized for its photocatalytic activity but was later discovered to be promising for the separation of CO₂ from wet flue gases. (13) MOF SBMOF-1 was synthesized to capture CO₂ but turned out to be an excellent material for separating Xe from Kr. (14) UMCM-152 was first reported in 2010 and tested for H₂ adsorption (15) but was rediscovered as a record-breaking material for oxygen storage eight years later. (16) In these and further examples, (17) computational screening studies discovered the potential of existing materials for new applications. Since the number of available materials is so large (and becomes even larger when including materials generated in silico (18)), computational modeling is at present the only feasible screening method.

A typical computational screening study aims to rank a set of materials for a given application: the first step is to determine key performance indicators (KPIs) and the ranking criteria for the comparison of different materials. KPIs are typically related to material properties, such as the electronic band structure (for optical or electronic KPIs), or adsorption isotherms (for KPIs related to gas storage or separations). While some properties, such as stability, remain difficult to predict from first-principles, density functional theory (DFT) calculations provide access to a wide range of properties of MOFs, including the band gap and band structure, (19) mechanical properties, (20,21) and catalytic properties. (22,23) DFT also allows us to make accurate predictions of the interactions of guest molecules inside the pores. (24,25) In addition, classical molecular simulations enable the computation of thermodynamic and transport properties of these guest molecules. (26,27)

When screening studies involve large numbers of materials and multiple steps, inspecting each simulation step manually is no longer feasible. It becomes necessary to develop robust workflows that provide automatic fallback routes for common errors, signal potential issues to the user (e.g., related to the atomic structures provided as input), manage calculations with a variety of software packages, and allow for easy retrieval of the resulting data. The development of automated workflows is a major effort, and the community would benefit enormously from open-source projects that allow the sharing of such tools.

The development of automated workflows is a major effort, and the community would benefit enormously from open-source projects that allow the sharing of such tools.

We can envision taking this approach even one step further: What if the workflow infrastructure was made available for experimental groups to use? They could upload the crystal structure of a new nanoporous material (MOF, COF, or zeolite) and—with close to zero effort—obtain calculations of thermodynamic and transport properties for a range of guest molecules, as well as predictions of how this new material would perform in screening studies previously published in the literature (Figure 2), or if an experimental group develops a novel separation process, having a database of thermodynamic data would allow this group to identify top performing materials for their applications. Finally, if a computational group improves an existing force field or protocol for a specific class of materials, the updated workflow could be available whenever a material of that class is uploaded.

Figure 2. Scheme of exemplary workflow. The user starts by uploading the atomic structure of a crystalline materials in the CIF format, which triggers the refinement of the atomic positions, the computation of pore geometry, and thermodynamic and transport properties. Finally, its performance for specific applications is evaluated, and the material is ranked versus other candidates.

In this Outlook, we introduce the challenge of matching nanoporous materials and applications and argue that an open-science platform is a promising and practical approach to address this need. Looking back at almost two decades of progress in the study and modeling of MOFs and COFs, we observe that it is often difficult to build upon and extend the output of the computational community. While many authors nowadays make the source code underlying their screening studies openly available, the barrier to putting them into action remains high for anyone who is not a computational expert. We suggest that most of the puzzle pieces are already there and, if put together, they have the potential to dramatically increase the impact of computational studies, both by activating new classes of users and by encouraging collaboration in the design of computational modules.

Most of the puzzle pieces are already there and, if put together, they have the potential to dramatically increase the impact of computational studies.

Databases of Nanoporous Materials

ARTICLE SECTIONS

Jump To

Curated Structures from Experimental Syntheses

Computational screening studies rely on large databases of materials. A first step is to collect all the reported structures in a consistent format: today, the Crystallographic Information File (CIF) format is the most common one. The minimal information needed to proceed with a computational screening study is the dimensions of the unit cell and the elements and coordinates of the atoms that compose the framework. This information is obtained ideally from single crystal X-ray diffraction studies. When obtaining single crystals is not possible, one can rely on powder X-ray diffraction or other indirect measurements instead. (28)

In the MOF community, it is standard practice to publish new structures in the Cambridge Structural Database (CSD) (29) and to report the reference code assigned to the entry in the article. With its more than one million entries (102 508 of which were recognized as MOFs until May 2020), (9) the CSD is the oldest and largest data set of organic and metal–organic crystals. (30)

Unfortunately, many of the reported structures in the CSD are not suitable for a computational screening study out of the box. From X-ray diffraction data, it is difficult to locate hydrogen. If the material is charged, locating the counterions can also be challenging. For porous MOFs, the crystal structure is often determined with solvent molecules present inside the framework, while many practical applications require activating the material by removing the solvent molecules. In addition, disorder in the material is often indicated via partial occupancies, which need to be resolved to unique structures (in most of the cases manually) before using the structures as input for simulations.

The group around D. Sholl pioneered the extraction of MOFs from the CSD for a computational screening purpose. In two studies from 2012 (seeking materials for kinetic separation of noble gases (31) and CO₂/N₂ (32)) they distilled a set of 3432 and 1163 MOFs, respectively, from which they discarded entries with atomic disorder, and they algorithmically removed solvent molecules. One year later, Siegel et al. (33) targeted hydrogen storage and identified ca. 38 800 crystals from the CSD as MOFs but had to exclude ca. 16 000 problematic structures due to missing H, disorder, etc. For these first studies, the final database of filtered and curated CIFs was only accessible upon request to the authors. In 2014, Chung et al. created a set of 5109 “Computation-Ready Experimental” (CoRE) structures, selected to be three-dimensional, porous (i.e., with a pore limiting diameter >2.4 Å), and fully desolvated, and made the database openly available for download. (34) Recently, this database was updated to include 14 142 MOFs, 546 of which were collected from sources other than the CSD. (10) This update also included a version of the database where solvent molecules coordinated to metal sites were not removed (i.e., the MOFs were not “computationally activated”). In two separate projects, Nazarian et al. used DFT to provide partial charges (35) and geometry-optimized structures (36) for the first set of CoRE-MOFs. Only 502 (i.e., ca. 10%) passed both refinements. The database with partial charges was used by other groups in several screening studies, (16,37−39) demonstrating the impact of providing an open-access, curated, and extensive database of structures to the computational community.

Ideally, for every new MOF structure deposited in the CSD, a computation-ready structure would be generated as well. At present, however, there is no standardized protocol for these steps—e.g., removal of solvents, addition of missing hydrogen atoms, resolution of partial occupancies, correction of atomic overlaps, and structural distortion—and as a result, each group may generate slightly different structures that make it difficult to compare predicted properties. (40,41) This cleaning procedure can be seen as a continuous process where more and more checks and fixes are added in a collaborative effort. (42,43) For the platform we envision, it would be highly desirable to eventually arrive at an internally consistent and extensive database of nanoporous structures that are “ready” for molecular simulations or electronic structure calculations, and made available in a way that satisfies the FAIR data principles: Findable, Accessible, Interoperable, and Reusable. (44,45)

Extending this curation to different classes of materials, such as COFs, inevitably results in new considerations and challenges. For MOFs, the CSD imposes quality controls on the accuracy of the crystal structure. COFs typically have short-range crystallinity but long-range disorder, preventing the refinement of the crystal structure directly from X-ray diffraction data (46) and thus inclusion in the CSD. As a consequence, experimental groups develop their own protocols to generate the crystal structures reported with their publications. These difficulties motivated us to create a database that combines the advantages of both the CoRE and CSD protocols and provides a high level of transparency and consistency in the refinements including cell optimization and the calculation of partial charges. Branching off from the second version of the CoRE-COF database by Tong et al., (47) we extended the database to 574 COFs in the June 2020 update. The relevant literature is monitored by the @COF_Papers Twitter bot, and structures in CIF format are collected in a public repository, where researchers can suggest new additions or report errors. (12) All modifications, corrections, and additions are tracked by the Git version control system. Moreover, an automated routine, orchestrated by the AiiDA workflow manager, (48,49) computes the DFT-optimized structures and partial charges following a published protocol. (11) The results are made available periodically in the CURATED COF database hosted on the Materials Cloud open science platform. (50) A recent independent study compared the gas-separation performances as computed from the structures of this database and the original COF structures, highlighting the importance of the curation process. (51)

Hypothetical Structures

In addition to the databases of experimentally determined structures, there is an even larger number of structures generated in silico, which are further candidates for computational screenings. Replacing the experimental synthesis of new materials with computational algorithms increases the number of atomic structures that can be assembled (zeolites, MOFs, and COFs) by orders of magnitude. To give an idea of how large these databases can get, we just mention two very recent works, which reported 325 000 hypothetical MOFs (13) and 471 990 hypothetical COFs. (52)

As the growth of the number of hypothetical structures even outpaces the continued increase of computational power, brute force screening will become increasingly unfeasible. A promising alternative is to select only a modest subset of most diverse structures to perform accurate calculations (comparable to those on experimental structures), train machine learning methods to capture the structure–performance relations, and use them to extend the screening to the remaining materials. (53) Indeed, the key to the success of this approach is to find effective metrics for the “diversity” between structures in the context of a particular application. (54)

Computation of Materials’ Properties

ARTICLE SECTIONS

Jump To

Gas Adsorption Properties

Once one has a set of computation-ready structures, one can start computing the properties that are relevant for the application(s) of interest—here, gas adsorption in nanoporous materials. If interested in comparing properties and performances among many materials (and updating this ranking over time), one needs to pay particular attention to the consistency of results. Consistency means, for example, applying the same protocol to curate the crystals’ atomic structure, to estimate partial charges, to exclude inaccessible pores, etc. in order to enable the comparison of the final results. This includes both choices of the model, such as the DFT functional or the force field (UFF, DREIDING, TraPPE, etc.), as well as secondary parameters, such as the choice of the DFT basis set or whether to use tail-corrections in grand canonical Monte Carlo (GCMC) adsorption calculations. (55)

A first step may involve a relaxation of the atomic positions using force fields, semiempirical methods, or DFT in order to ensure that the atomic structure is consistent with the computational method employed. This step can also help identify mistakes in input structures and take the effect of solvent removal on the framework into account.

Gas–framework interactions are often evaluated using GCMC insertion techniques with classical force fields. (17) In this approach, the Coulomb interaction is modeled by partial charges, which are tabulated for popular gas molecules but need to be computed for the framework. If DFT was used for the geometry relaxation, partial charges can be computed at negligible extra cost from the electrostatic potential, usually preferring protocols that aim at reproducing the electrostatic potential (e.g., REPEAT, DDEC) over the others (e.g., Mulliken, Hirshfeld, Bader). (56,57) Alternatively, cheaper charge equilibration methods can be used, but with extreme care (see ref (37)). The partial charges on the framework atoms need to be combined with a force field to describe the interaction between the gas molecule and the framework. Many studies opt for off-the-shelf parameters for the dispersion interaction, such as DREIDING (58) or UFF (59) for the framework and TraPPE (60) for the adsorbate. Steps outside the original design space of existing force fields or modifications of their parameters need to be carefully validated in order to ensure that the behavior of the gas molecules in the pores is reproduced with sufficient accuracy (e.g., adsorption isotherms, heats of adsorption, etc.).

As one moves to larger numbers of structures and more complex workflows, it becomes increasingly challenging to manage the calculations and to provide all information required to reproduce a particular result. This is where workflow managers can come to the rescue, and numerous open-source infrastructures are available for orchestrating computational chemistry codes with advanced logic, (61) such as AiiDA, (48,49) FireWorks, (62) AFLOW, (63) or signac. (64)

Open Challenges

Once we obtain a reliable force field for molecule–framework interactions, we are still left with a number of open challenges. One challenge is the modeling of defects: as high-throughput computations typically assume perfect crystals, they will not capture properties that are dominated by crystal defects present in the experimental material. Another challenge is the modeling of framework mechanics upon adsorption: most screening studies assume a rigid framework. For many structures, this approximation is reasonable, but some materials are known to display structural changes upon gas adsorption, which can affect performance in relevant applications. (65) Assuming the structure to be rigid may lead to incorrect identification of pore accessibility for gas molecules. Algorithms based on geometrical assessment of channel diameters can easily recognize nonaccessible pores and exclude them from the adsorption calculation. (66) However, it is less trivial to routinely identify those cases where a small rotation of the ligands can allow the gas molecule to permeate (such as in the well-studied case of ZIF-8 (67,68)).

There are other material properties relevant to the process modeling of gas-related applications that can be evaluated from the unit cell, such as gas diffusion, (69) heat capacity, (70,71) mechanical stability, (72,73) and chemical stability. The studies cited above propose computational protocols for investigating these properties, which might be extended for high-throughput screenings. Combining all these properties in the same screening platform would allow the filtering out of structures that are unstable or show poor thermal or molecular diffusion and provide more information to the process model.

Moving beyond the field of gas adsorption brings yet more properties into focus, such as more accurate electronic properties for applications in sensing, semiconductors, and photocatalysis, (19,74) which put increased emphasis on the choice of the electronic structure method and are beyond the scope of this Outlook.

Ranking Materials

ARTICLE SECTIONS

Jump To

Accurately predicting material properties is the aim of molecular simulations, but it represents only half of the story: our ultimate goal is to rank materials for a given application, based on key performance indicators (KPIs). In the following, we discuss the KPIs for two important applications of nanoporous materials: hydrogen storage (33,75−79) and CO₂ separation from nitrogen. (11,40,80−83)

Our ultimate goal is to rank materials for a given application, based on key performance indicators

For H₂ storage, the main KPI is the deliverable (or “working”) capacity, i.e., the difference in gas uptake between the loading conditions at higher pressure and/or lower temperature, and the discharging conditions at lower pressure and/or higher temperature. Therefore, the evaluation of hydrogen storage performance requires calculations at only these two conditions of temperature and pressure, and molecular simulations have been shown to be feasible for screening more than half a million structures. (78,79) Similar considerations are also valid for the evaluation of natural gas deliverable capacity. (34,47,84,85) Other important KPIs may focus on the diffusion of gas and heat inside the framework, in order to enable fast loading/discharge and heat dissipation.

For CO₂ capture, finding KPIs for the ranking is more complex. In 2012, our group developed a simplified thermodynamic model for carbon capture and sequestration (CCS) involving a temperature–pressure-swing adsorption process, considering inlet gases from a coal-fired power plant (14:86 ratio of CO₂:N₂), a natural-gas-fired power plant (4% CO₂), or air (400 ppm of CO₂). This model was used to evaluate different classes of nanoporous materials, (82,86) and we recently expanded the study to COFs. (11) Two KPIs were identified: The “parasitic energy” is defined as the energy needed to separate 1 kg of CO₂ and compress the purified gas to 150 bar for underground storage. The parasitic energy can be taken as a measure of the operating cost of the separation (OPEX). The working capacity, on the other hand, determines the amount of adsorbent material needed and thus the capital cost (CAPEX). The study showed that the minimal parasitic energy can be related to an optimal value for the Henry coefficient of CO₂ around 10^–3 mol/(kg Pa) (at 300 K) for power plants—stronger affinity between CO₂ and the framework would result in higher energy needed for the regeneration of the adsorbent. For direct-air capture, the optimal value lies above 10^–1 mol/(kg Pa), and chemisorption appears to be a more promising solution. Recently, simulations have been coupled with more advanced models of the pressure-swing process, (87−89) indicating subtle relations between the properties of the material and their performance in the process. In particular, the often overlooked nitrogen isotherm was identified as a key indicator.

The case of CO₂ separation highlights the importance of connecting materials’ properties to process modeling: on one hand, the process modelers need to be aware of the uncertainties in material property predictions and how they propagate through their model. If small perturbations in the inputs alter the outcome significantly, this “butterfly effect” will compromise the reliability of the final ranking. On the other hand, the molecular simulation community should focus its efforts on improving the predictive accuracy for those properties that are shown to have the largest influence on the process models. In this context, modular workflows and automated provenance tracking can simplify investigations of individual workflow components and help trace their impact on the final rankings.

Toward Best Practices

ARTICLE SECTIONS

Jump To

While the vision of a common platform with easily extendable and fully interoperable workflows may appear somewhat utopian today, there are a number of concrete practices that researchers can adopt to move closer toward this goal.

Reproducibility

In order for a reader of a scientific publication to be able to reproduce its results, the study should report—among the analysis and discussion of its scientific results—also all the information needed to reproduce them. However, for screening studies that involve large numbers of materials and/or multistep workflows, achieving this “radical transparency” is easier said than done: manually collecting all necessary input files, postprocessing scripts, software versions, etc. can be time-consuming, and completeness is difficult to ensure. Here, workflow managers can help by tracking the provenance automatically and providing ways to export and share this information with peers.

For example, our recent work on parsing COFs from the literature and assessing their performance for carbon capture tries to follow this approach, publishing both the full provenance graph of the study and the source code of the workflow used to orchestrate the calculations. (11,50,90) The provenance graph gives any interested researcher the ability to click on a data point and to inspect every step of the workflow that was used to compute it, try to reproduce an individual calculation themselves, or report mistakes they encounter. Sharing the source code of the corresponding workflows on collaborative platforms like GitHub further enables direct suggestions of bug fixes or improvements to the protocols, both in code and in narrative form.

The provenance graph gives any interested researcher the ability to click on a data point and to inspect every step of the workflow that was used to compute it.

Automation

Moving from the study of a few materials to hundreds or thousands of them puts an emphasis on automation. One needs an effective way not only to manage the sequence of calculations but also to handle common errors and perform preliminary data analysis. We illustrate this using simple, practical examples from gas adsorption in nanoporous materials: Before submitting a crystal structure to GCMC simulations one has to detect and block the inaccessible pores and expand the simulation cell to include twice the cutoff used for the potential. These operations may need some external packages or ad hoc scripts and can be fully automated using a workflow manager. Another notable case is the handling of DFT calculations in which the self-consistent field cycle fails to converge. Depending on the system under study, remedies can include automatic resubmission with slower, more conservative minimization schemes (e.g., switching from orbital transformation to diagonalization methods) or turning on electronic smearing. (11)

When considering one’s own use cases, and realizing the many intermediate steps that would need to be automated to go from an input structure to the final result, one inevitably arrives at the question whether the effort of full automation is worth the time investment. While this determination needs to be made case by case, it is easy to forget that each manual operation makes results harder to reproduce and entails substantial time investments when others (or even our future self) go on to extend and build upon the work. At the same time, modern workflow managers provide time-saving convenience features, such as automatic translations of job parameters to the language of various queuing systems, automatic file transfers between the local workstation and the cluster, and automatic record keeping.

The development of a robust workflow can be challenging, but is a valuable outcome from a computational study on its own: it ensures that when new sets of materials are released, they can be included in the screening with minimal additional effort.

Open Source

The idea of open science does not stop at access to papers and data but extends naturally to the software used to obtain the data: the use of free and open-source software (FOSS) lowers the barriers to reusing, reproducing, and building upon prior work. This is particularly true for materials screening studies, where readers may want to compare a new material to the set of the already screened ones. When data, software, and workflows are made openly accessible, the barrier for such checks reduces to the marginal computational cost of screening just one more material.

Despite these obvious benefits, the demand for FOSS has been notably missing from declarations in the open science context. (91) One of the reasons may be that developing and maintaining high-quality scientific software takes years of teamwork, and commercial licenses have proven to be a successful model for funding such efforts in the past. (92) Today, however, FOSS alternatives exist for most applications in computational materials science, and we do seem to observe a trend of increasing adoption of these codes vs their commercial competitors over the course of the past decade: (92,93) CASTEP (94,95) (restricted to academic use) and openMolcas (96) being two recent examples of codes that have decided to switch to a more open licensing model.

We believe that the question of sustainable software development for open science needs to be on the table and discussed by all stakeholders.

Setting the Stage for Machine Learning

In recent years, machine learning (ML) has been rapidly mixing with molecular simulations, (97) and we expect the advent of automated workflows in the field of nanoporous materials modeling to amplify this trend. (53) Among the first applications of ML methods is the prediction of the Henry coefficient or a full isotherm in a fraction of a second, from conventional geometric properties of the crystal structure (such as pore volume and atoms’ connectivity) and/or more advanced descriptors. (98−101) This massive speed up enables the screening of even millions of materials at affordable computational cost, shifting the role of molecular simulation to providing sufficient training data for the ML. The main question for a new material then becomes is this structure different enough from the others already included in the training set to justify the use of expensive molecular simulations over ML predictions? (54)

However, at present, ML studies trained on data published by other groups are rare in the field. In many cases, data are recomputed specifically for the training, even when similar (but not identical and consistent!) data are available. In this context, moving as a community from delivering just a final set of results to including also the infrastructure needed to obtain them could allow ML experts to easily extend the training set with new consistent data. Reusing the same data sets in multiple ML studies would also enable effective assessments of the models themselves, which is less trivial when the training data differ. Finally, the training routines should be automated and made reproducible as well. (53)

Toward a Prototype of a Materials Matching Platform

ARTICLE SECTIONS

Jump To

As a first step toward realizing the ideas put forward in this Outlook, we have extended our work of curating COFs and screening these materials for carbon capture (11) to six new applications and 250 new COFs. (50) The new structures include mostly COFs published after the original work (as tracked by the @COF_PAPERS Twitter bot), and the applications are based on previous screening studies focused on gas storage (methane, (85) hydrogen, (78,79,102) and oxygen (16)) and gas separations (Xe/Kr, (14) H₂S removal in wet gases).

Figure 3. Performance of COF structures for CO₂ capture: parasitic energy required for the process versus gravimetric working capacity. Markers of the 250 new COFs are color-coded based on their ranking from high performance (low parasitic energy and high working capacity, green) to low performance (red). Markers of materials already included in ref (11) are shown in light gray.

Provided that the input structure is chemically sound (e.g., no missing hydrogens or overlapping atoms) and is charge-neutral (no counterbalancing ions), the workflow CURATED 99% of the structures without human intervention. For all CURATED structures, we automatically computed the adsorption isotherms and/or Henry coefficients of CO₂, N₂, H₂, CH₄, O₂, H₂S, H₂O, Xe, and Kr. From these isotherms, the KPIs were computed automatically and used to rank the materials as shown in Figure 3 for the extension of our previous study on CO₂ capture (11) and in Figure 4 for the other new applications included. The full workflow typically takes 2–5 days from start to finish, using ≈1000 core hours. In other words, it costs about the price of three cups of coffee: two cups for the curation of the structure and one for all KPIs. (103) The full provenance graph of each workflow, shown in Figure 5, is tracked automatically by the AiiDA workflow manager.

Figure 4. Performance of CURATED-COFs for H₂ storage at (a) cryogenic and (b) near-ambient conditions, (c) methane storage, (d) oxygen storage, (e) Xe/Kr separation, and (f) (H₂S)/water separation. The ranking is color-coded from high performance (green) to low performance (red). Selectivities are computed as the ratio of the Henry coefficients of the two gases at 300 K. The coordinates of the markers for T-COF-2 and JUC-509 are highlighted by dashed and solid lines, respectively.

Figure 5. AiiDA provenance graph of the workflow tracing the entire path from the initial CIF file to the properties and performance computed for it. The graph shows process and data as nodes, and their connection: (49) in an interactive visualization, each node can be browsed to explore the input parameters of the calculation, its output results, and the details of the processes. (104) Colors distinguish different modules of the workflow, whose source code is available online. (90) The modules make use of other popular open-source tools, such as CP2K, (105) Raspa, (106) Zeo++, (66) and chargemol. (107)

It is interesting to discuss two examples of recently reported structures that were included in the update. T-COF-2 (Figure 6a) was synthesized in 2020 and tested for a photocatalysis application. (108) The simulations do not predict this material to be among the top performers for any of the gas adsorption applications implemented so far. While this is the most likely outcome, as the screening studies are extended to more applications, the probability of discovering unexpected hits should increase.

Figure 6. Crystal structures of (a) T-COF-2 and (b) JUC-509. Elements: H (white), C (gray), N (blue), oxygen (red), S (yellow), Cl (green).

The other COF, JUC-509 (Figure 6b), seems more promising. This material was synthesized in 2019 for catalysis. (109) Based on the atomic structure of the material, our screening predicts it to be among the top performing materials for the storage of H₂, CH₄, and O₂ (Figure 4). We acknowledge that there are other factors that may play a role in deciding whether it is worth testing JUC-509 for these applications, but it is our hope that cases like this one will lead to interesting, unexpected discoveries going forward.

Many things remain to be done in order to transform this prototype into a platform of broad impact. We have limited ourselves to COFs, and it is essential to extend it to MOFs and other porous materials. We have used relatively elementary KPIs to illustrate the concept, which we hope to replace with more advanced ones, and so far, the predictions rely on generic force fields which may not always be the optimal choice. Finally, we would like to extend the range of applications beyond the current scope of gas storage and separation. The results of this screening are updated periodically and can be accessed from materialscloud.org/discover/curated-cofs. Both the data and the source code of the underlying workflows are made available online. (110)

Over time, we hope to inspire other research groups to build upon the existing open infrastructure and develop their own modules for new applications, resulting in “living” screening studies that are regularly updated with new materials. Infrastructure projects like these require long-term commitments, which are notoriously difficult to make in today’s research funding landscape. Thanks to support from the MARVEL National Centre of Competence for Research, we feel ready to accept the challenge and, given the enormous potential impact for the field, hope to be able to convince other funding agencies and possibly commercial partners to join.

In summary, the idea of this Outlook is to illustrate a dormant potential in the computational materials science community that can be unlocked by moving toward a more open, collaborative way of doing science—not necessarily inventing something spectacularly new, but simply putting together the pieces of a large puzzle. While we have made the case for the field of nanoporous materials for gas adsorption applications, the basic concept would seem extensible to further classes of materials and applications.

Author Information

ARTICLE SECTIONS

Jump To

Corresponding Author
- Berend Smit - Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland; http://orcid.org/0000-0003-4653-8562; Email: [email protected]
Authors
- Daniele Ongari - Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland; http://orcid.org/0000-0001-6197-2901
- Leopold Talirz - Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, Sion, CH-1951 Valais, Switzerland; Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; http://orcid.org/0000-0002-1524-5903
Notes
The authors declare no competing financial interest.

Acknowledgments

ARTICLE SECTIONS

Jump To

The research in this Outlook was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement 666983, MaGic) and the MARVEL National Centre for Competence in Research funded by the Swiss National Science Foundation (grant agreement ID 51NF40-182892) and is part of the PrISMa Project (299659), which is funded through the ACT programme (Accelerating CCS Technologies, Horizon2020 Project 294766). Financial contributions made from Department for Business, Energy & Industrial Strategy (BEIS) together with extra funding from NERC and EPSRC Research Councils, United Kingdom; The Research Council of Norway, (RCN), Norway; Swiss Federal Office of Energy (SFOE), Switzerland; and US-Department of Energy (US-DOE), USA, are gratefully acknowledged. Additional financial support from TOTAL and Equinor is also gratefully acknowledged.

Acronyms

ARTICLE SECTIONS

Jump To

AiiDA	Automated Interactive Infrastructure and DAtabase for computational science
CIF	crystallographic information file
COF	covalent organic framework
CoRE	computation-ready experimental
CSD	Cambridge Structural Database
CURATED	Clean, Uniform, Refined with Automated Tracking from Experimental Database
DFT	density functional theory
GCMC	grand canonical Monte Carlo
KPI	key performance indicator
ML	machine learning
MOF	metal–organic framework

References

ARTICLE SECTIONS

Jump To

This article references 110 other publications.

1
Wang, C.; Wang, Y.; Ge, R.; Song, X.; Xing, X.; Jiang, Q.; Lu, H.; Hao, C.; Guo, X.; Gao, Y.; Jiang, D. A 3D covalent organic framework with exceptionally high iodine capture capability. Chem. - Eur. J. 2018, 24, 585– 589, DOI: 10.1002/chem.201705405
[Crossref], [PubMed], [CAS], Google Scholar
1
A 3D Covalent Organic Framework with Exceptionally High Iodine Capture Capability
Wang, Chang; Wang, Yu; Ge, Rile; Song, Xuedan; Xing, Xueqing; Jiang, Qike; Lu, Hui; Hao, Ce; Guo, Xinwen; Gao, Yanan; Jiang, Donglin
Chemistry - A European Journal (2018), 24 (3), 585-589CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)
Using porous materials to cope with environmental issues is promising but remains a challenge esp. for removing the radioactive vapor wastes in fission because of harsh adsorption conditions. Here we report a new, stable covalent org. framework (COF) as a porous platform for removing iodine vapor-a major radioactive fission waste. The three-dimensional COF consists of a diamond topol. knotted by adamantane units, creates ordered one-dimensional pores and are highly porous. The COF enables the removal of iodine vapor via charge transfer complex formation with the pore walls to achieve exceptional capacity. Moreover, the 3D COF is "soft" to trigger structural fitting to iodine while retaining connectivity and enables cycle use for many times while retaining high uptake capacity. These results set a new benchmark for fission waste removal and suggest the great potential of COFs as a designable porous material for challenging world-threatening pollution issues.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhvFyjsbbE&md5=3e09a97792181c87badfdf7f38d4d39d
2
Mason, J. A.; Veenstra, M.; Long, J. R. Evaluating metal–organic frameworks for natural gas storage. Chem. Sci. 2014, 5, 32– 51, DOI: 10.1039/C3SC52633J
[Crossref], [CAS], Google Scholar
2
Evaluating metal-organic frameworks for natural gas storage
Mason, Jarad A.; Veenstra, Mike; Long, Jeffrey R.
Chemical Science (2014), 5 (1), 32-51CODEN: CSHCCN; ISSN:2041-6520. (Royal Society of Chemistry)
Metal-org. frameworks have received significant attention as a new class of adsorbents for natural gas storage; however, inconsistencies in reporting high-pressure adsorption data and a lack of comparative studies have made it challenging to evaluate both new and existing materials. Here, we briefly discuss high-pressure adsorption measurements and review efforts to develop metal-org. frameworks with high methane storage capacities. To illustrate the most important properties for evaluating adsorbents for natural gas storage and for designing a next generation of improved materials, six metal-org. frameworks and an activated carbon, with a range of surface areas, pore structures, and surface chemistries representative of the most promising adsorbents for methane storage, are evaluated in detail. High-pressure methane adsorption isotherms are used to compare gravimetric and volumetric capacities, isosteric heats of adsorption, and usable storage capacities. Addnl., the relative importance of increasing volumetric capacity, rather than gravimetric capacity, for extending the driving range of natural gas vehicles is highlighted. Other important systems-level factors, such as thermal management, mech. properties, and the effects of impurities, are also considered, and potential materials synthesis contributions to improving performance in a complete adsorbed natural gas system are discussed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVGntLvE&md5=05a99cd7be9ef1819aca42d1c36f1f1d
3
Zhu, L.; Liu, X.-Q.; Jiang, H.-L.; Sun, L.-B. Metal–Organic Frameworks for Heterogeneous Basic Catalysis. Chem. Rev. 2017, 117, 8129, DOI: 10.1021/acs.chemrev.7b00091
[ACS Full Text ], [CAS], Google Scholar
3
Metal-Organic Frameworks for Heterogeneous Basic Catalysis
Zhu, Li; Liu, Xiao-Qin; Jiang, Hai-Long; Sun, Lin-Bing
Chemical Reviews (Washington, DC, United States) (2017), 117 (12), 8129-8176CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. Great attention has been given to metal-org. frameworks (MOFs)-derived solid bases because of their attractive structure and catalytic performance in various org. reactions. The extraordinary skeleton structure of MOFs provides many possibilities for incorporation of diverse basic functionalities, which is unachievable for conventional solid bases. The past decade has witnessed remarkable advances in this vibrant research area; however, MOFs for heterogeneous basic catalysis have never been reviewed until now. Therefore, a review summarizing MOFs-derived base catalysts is highly expected. In this review, we present an overview of the recent progress in MOFs-derived solid bases covering prepn., characterization, and catalytic applications. In the prepn. section, the solid bases are divided into two categories, namely, MOFs with intrinsic basicity and MOFs with modified basicity. The basicity can originate from either metal sites or org. ligands. Different approaches used for generation of basic sites are included, and each approach is described with representative examples. The fundamental principles for the design and fabrication of MOFs with basic functionalities are featured. In the characterization section, exptl. techniques and theor. calcns. employed for characterization of basic MOFs are summarized. Some representive exptl. techniques, such as temp.-programmed desorption of CO2 (CO2-TPD) and IR (IR) spectra of different probing mols., are covered. Following prepn. and characterization, the catalytic applications of MOFs-derived solid bases are dealt with. These solid bases have potential to catalyze some well-known "base-catalyzed reactions" like Knoevenagel condensation, aldol condensation, and Michael addn. Meanwhile, in contrast to conventional solid bases, MOFs show some different catalytic properties due to their special structural and surface properties. Remarkably, characteristic features of MOFs-derived solid bases are described by comparing with conventional inorg. counterparts, keeping in mind the current opportunities and challenges in this field.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXotlaku7o%253D&md5=b4be0fef2c9454a53492290865537878
4
Bavykina, A.; Kolobov, N.; Khan, I. S.; Bau, J. A.; Ramirez, A.; Gascon, J. Metal–Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives. Chem. Rev. 2020, 120, 8468, DOI: 10.1021/acs.chemrev.9b00685
[ACS Full Text ], [CAS], Google Scholar
4
Metal-Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives
Bavykina, Anastasiya; Kolobov, Nikita; Khan, Il Son; Bau, Jeremy A.; Ramirez, Adrian; Gascon, Jorge
Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8468-8535CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. More than 95% (in vol.) of all of today's chem. products are manufd. through catalytic processes, making research into more efficient catalytic materials a thrilling and very dynamic research field. In this regard, metal-org. frameworks (MOFs) offer great opportunities for the rational design of new catalytic solids, as highlighted by the unprecedented no. of publications appearing over the past decade. In this review, the recent advances in the application of MOFs in heterogeneous catalysis are discussed. MOFs with intrinsic thermocatalytic activity, as hosts for the incorporation of metal nanoparticles, as precursors for the manuf. of composite catalysts and those active in photo- and electrocatalytic processes are critically reviewed. The review is wrapped up with our personal view on future research directions.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlslOns7o%253D&md5=857333854eb405b199bd222354bd6218
5
Liu, X.; Huang, D.; Lai, C.; Zeng, G.; Qin, L.; Wang, H.; Yi, H.; Li, B.; Liu, S.; Zhang, M.; Deng, R.; Fu, Y.; Li, L.; Xue, W.; Chen, S. Recent advances in covalent organic frameworks (COFs) as a smart sensing material. Chem. Soc. Rev. 2019, 48, 5266– 5302, DOI: 10.1039/C9CS00299E
[Crossref], [PubMed], [CAS], Google Scholar
5
Recent advances in covalent organic frameworks (COFs) as a smart sensing material
Liu, Xigui; Huang, Danlian; Lai, Cui; Zeng, Guangming; Qin, Lei; Wang, Han; Yi, Huan; Li, Bisheng; Liu, Shiyu; Zhang, Mingming; Deng, Rui; Fu, Yukui; Li, Ling; Xue, Wenjing; Chen, Sha
Chemical Society Reviews (2019), 48 (20), 5266-5302CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
A review. As a newly emerging kind of porous material, covalent org. frameworks (COFs) have drawn much attention because of their fascinating structural features (e.g., divinable structure, adjustable porosity and total org. backbone). Since the seminal work of Yaghi and co-workers reported in 2005, the COF materials have shown superior potential in diverse applications, such as gas storage, adsorption, optoelectronics, catalysis, etc. Recently, COF materials have shown a new trend in sensing fields. This crit. review briefly describes the synthesis routes for COF powders and thin films. What's more, the most fascinating and significant applications of COFs in sensing fields including explosive sensing, humidity sensing, pH detection, biosensing, gas sensing, metal ion sensing, and other substance sensing are summarized and highlighted. Finally, the major challenges and future trends of COFs with respect to their prepn. and sensing applications are discussed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1Oms7zM&md5=3bf2091e122fdc08d3e757c4d0ea5f77
6
Kreno, L. E.; Leong, K.; Farha, O. K.; Allendorf, M.; Van Duyne, R. P.; Hupp, J. T. Metal–Organic Framework Materials as Chemical Sensors. Chem. Rev. 2012, 112, 1105– 1125, DOI: 10.1021/cr200324t
[ACS Full Text ], [CAS], Google Scholar
6
Metal-Organic Framework Materials as Chemical Sensors
Kreno, Lauren E.; Leong, Kirsty; Farha, Omar K.; Allendorf, Mark; Van Duyne, Richard P.; Hupp, Joseph T.
Chemical Reviews (Washington, DC, United States) (2012), 112 (2), 1105-1125CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. The authors present a crit. review of the literature on metal-org. frameworks (MOFs) as chem. sensors. The authors begin by briefly examg. challenges relating to MOF sensor development including the design of MOFs with desirable properties, incorporation of appropriate signal transduction capabilities, and integration of MOFs into devices by employing thin-film growth techniques. Subsequent sections discuss specific examples of MOF sensors, categorized by method of signal transduction. Sensors based on MOF photoluminescence are discussed briefly. The authors have limited the review of luminescence-based sensors to a small no. of recent reports where the porous MOF architecture, or its chem. compn., imparts selective sensing capabilities. Scintillating MOFs that luminesce in the presence of radioactive analytes are also discussed. Other signal transduction schemes that use photons include various kinds of optical interferometry, analyte modulation of localized surface plasmon resonance energies, and solvatochromism. Mech. signal-transduction schemes employed with MOFs include ones based on surface acoustic wave, quartz crystal microbalance, and microcantilever devices. Elec. schemes thus far were limited to ones based on impedance spectroscopy.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVCgtL%252FI&md5=f6ed572725bc067ee8da81880bf1ec90
7
Burnham, J. F. Scopus database: a review. Biomed. Digit. Libr. 2006, 3, 1, DOI: 10.1186/1742-5581-3-1
[Crossref], [PubMed], [CAS], Google Scholar
7
Scopus database: a review
Burnham Judy F
Biomedical digital libraries (2006), 3 (), 1 ISSN:.
The Scopus database provides access to STM journal articles and the references included in those articles, allowing the searcher to search both forward and backward in time. The database can be used for collection development as well as for research. This review provides information on the key points of the database and compares it to Web of Science. Neither database is inclusive, but complements each other. If a library can only afford one, choice must be based in institutional needs.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD287nslKmsg%253D%253D&md5=e20a31e5cc40dca57d9087b9ed529da0
8
Database of Zeolite Structures. www.iza-structure.org/databases/ (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
9
Moghadam, P. Z.; Li, A.; Wiggin, S. B.; Tao, A.; Maloney, A. G. P.; Wood, P. A.; Ward, S. C.; Fairen-Jimenez, D. Development of a Cambridge structural database subset: a collection of metal-organic frameworks for past, present, and future. Chem. Mater. 2017, 29, 2618– 2625, DOI: 10.1021/acs.chemmater.7b00441
[ACS Full Text ], [CAS], Google Scholar
9
Development of a Cambridge Structural Database Subset: A Collection of Metal-Organic Frameworks for Past, Present, and Future
Moghadam, Peyman Z.; Li, Aurelia; Wiggin, Seth B.; Tao, Andi; Maloney, Andrew G. P.; Wood, Peter A.; Ward, Suzanna C.; Fairen-Jimenez, David
Chemistry of Materials (2017), 29 (7), 2618-2625CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
The generation and characterization of the most complete collection of metal-org. frameworks (MOFs) maintained and updated by the Cambridge Crystallog. Data Center (CCDC) is reported. To set up this subset, the question was asked what is a MOF and a no. of look-for-MOF criteria embedded within a bespoke Cambridge Structural Database (CSD) Python API workflow was implemented to identify and ext. information on 69,666 MOF materials. The CSD MOF subset is updated regularly with subsequent MOF addns. to the CSD, bringing a unique record for all researchers working in the area of porous materials around the world, whether to perform high-throughput computational screening for materials discovery or to have a global view over the existing structures in a single resource. Using this resource, the authors then developed and used an array of computational tools to remove residual solvent mols. from the framework pores of all the MOFs identified and went on to analyze geometrical and phys. properties of nondisordered structures.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXkt12rurc%253D&md5=377ebf2d805518194eb8cd0f9d3f3608
10
Chung, Y. G.; Haldoupis, E.; Bucior, B. J.; Haranczyk, M.; Lee, S.; Zhang, H.; Vogiatzis, K. D.; Milisavljevic, M.; Ling, S.; Camp, J. S.; Slater, B.; Siepmann, J. I.; Sholl, D. S.; Snurr, R. Q. Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019. J. Chem. Eng. Data 2019, 64, 5985– 5998, DOI: 10.1021/acs.jced.9b00835
[ACS Full Text ], [CAS], Google Scholar
10
Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal-Organic Framework Database: CoRE MOF 2019
Chung, Yongchul G.; Haldoupis, Emmanuel; Bucior, Benjamin J.; Haranczyk, Maciej; Lee, Seulchan; Zhang, Hongda; Vogiatzis, Konstantinos D.; Milisavljevic, Marija; Ling, Sanliang; Camp, Jeffrey S.; Slater, Ben; Siepmann, J. Ilja; Sholl, David S.; Snurr, Randall Q.
Journal of Chemical & Engineering Data (2019), 64 (12), 5985-5998CODEN: JCEAAX; ISSN:0021-9568. (American Chemical Society)
Over 14 000 porous, three-dimensional metal-org. framework structures are compiled and analyzed as a part of an update to the Computation-Ready, Exptl. Metal-Org. Framework Database (CoRE MOF Database). The updated database includes addnl. structures that were contributed by CoRE MOF users, obtained from updates of the Cambridge Structural Database and a Web of Science search, and derived through semiautomated reconstruction of disordered structures using a topol.-based crystal generator. In addn., value is added to the CoRE MOF database through new analyses that can speed up future nanoporous materials discovery activities, including open metal site detection and duplicate searches. Crystal structures (only for the subset that underwent significant changes during curation), pore analytics, and phys. property data are included with the publicly available CoRE MOF 2019 database.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitVOmtrrL&md5=51670c93eb8cb43309395afaaf620253
11
Ongari, D.; Yakutovich, A. V.; Talirz, L.; Smit, B. Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent–Organic Frameworks. ACS Cent. Sci. 2019, 5, 1663– 1675, DOI: 10.1021/acscentsci.9b00619
[ACS Full Text ], [CAS], Google Scholar
11
Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent-Organic Frameworks
Ongari, Daniele; Yakutovich, Aliaksandr V.; Talirz, Leopold; Smit, Berend
ACS Central Science (2019), 5 (10), 1663-1675CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
We present a workflow that traces the path from the bulk structure of a cryst. material to assessing its performance in carbon capture from coal's postcombustion flue gases. This workflow is applied to a database of 324 covalent-org. frameworks (COFs) reported in the literature, to characterize their CO2 adsorption properties using the following steps: (1) optimization of the crystal structure (at. positions and unit cell) using d. functional theory, (2) fitting at. point charges based on the electron d., (3) characterizing the pore geometry of the structures before and after optimization, (4) computing carbon dioxide and nitrogen isotherms using grand canonical Monte Carlo simulations with an empirical interaction potential, and finally, (5) assessing the CO2 parasitic energy via process modeling. The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA). Both the workflow and the automatically generated provenance graph of our calcns. are made available on the Materials Cloud, allowing peers to inspect every input parameter and result along the workflow, download structures and files at intermediate stages, and start their research right from where this work has left off. In particular, our set of CURATED (Clean, Uniform, and Refined with Automatic Tracking from Exptl. Database) COFs, having optimized geometry and high-quality DFT-derived point charges, are available for further investigations of gas adsorption properties. We plan to update the database as new COFs are being reported. An automated and reproducible computational workflow is proposed, to systematically optimize the geometry of covalent-org. frameworks and evaluate their performances for carbon capture and storage.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvVeqsL%252FM&md5=8f47a5e3d00532e7064d5259e73ab1f1
12
CURATED-COFs. github.com/danieleongari/egulp (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
13
Boyd, P. G. Data-driven design of metal–organic frameworks for wet flue gas CO2 capture. Nature 2019, 576, 253– 256, DOI: 10.1038/s41586-019-1798-7
[Crossref], [PubMed], [CAS], Google Scholar
13
Data-driven design of metal-organic frameworks for wet flue gas CO2 capture
Boyd, Peter G.; Chidambaram, Arunraj; Garcia-Diez, Enrique; Ireland, Christopher P.; Daff, Thomas D.; Bounds, Richard; Gladysiak, Andrzej; Schouwink, Pascal; Moosavi, Seyed Mohamad; Maroto-Valer, M. Mercedes; Reimer, Jeffrey A.; Navarro, Jorge A. R.; Woo, Tom K.; Garcia, Susana; Stylianou, Kyriakos C.; Smit, Berend
Nature (London, United Kingdom) (2019), 576 (7786), 253-256CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
Limiting the increase of CO2 in the atm. is one of the largest challenges of our generation1. Because carbon capture and storage is one of the few viable technologies that can mitigate current CO2 emissions2, much effort is focused on developing solid adsorbents that can efficiently capture CO2 from flue gases emitted from anthropogenic sources3. One class of materials that has attracted considerable interest in this context is metal-org. frameworks (MOFs), in which the careful combination of org. ligands with metal-ion nodes can, in principle, give rise to innumerable structurally and chem. distinct nanoporous MOFs. However, many MOFs that are optimized for the sepn. of CO2 from nitrogen4-7 do not perform well when using realistic flue gas that contains water, because water competes with CO2 for the same adsorption sites and thereby causes the materials to lose their selectivity. Although flue gases can be dried, this renders the capture process prohibitively expensive8,9. Here we show that data mining of a computational screening library of over 300,000 MOFs can identify different classes of strong CO2-binding sites-which we term 'adsorbaphores'-that endow MOFs with CO2/N2 selectivity that persists in wet flue gases. We subsequently synthesized two water-stable MOFs contg. the most hydrophobic adsorbaphore, and found that their carbon-capture performance is not affected by water and outperforms that of some com. materials. Testing the performance of these MOFs in an industrial setting and consideration of the full capture process-including the targeted CO2 sink, such as geol. storage or serving as a carbon source for the chem. industry-will be necessary to identify the optimal sepn. material.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitlOmu7zN&md5=ed26245f884c2d2fa86f6d4251be593a
14
Banerjee, D.; Simon, C. M.; Plonka, A. M.; Motkuri, R. K.; Liu, J.; Chen, X.; Smit, B.; Parise, J. B.; Haranczyk, M.; Thallapally, P. K. Metal–organic framework with optimally selective xenon adsorption and separation. Nat. Commun. 2016, 7, 11831, DOI: 10.1038/ncomms11831
[Crossref], [CAS], Google Scholar
14
Metal-organic framework with optimally selective xenon adsorption and separation
Banerjee, Debasis; Simon, Cory M.; Plonka, Anna M.; Motkuri, Radha K.; Liu, Jian; Chen, Xianyin; Smit, Berend; Parise, John B.; Haranczyk, Maciej; Thallapally, Praveen K.
Nature Communications (2016), 7 (), ncomms11831CODEN: NCAOBW; ISSN:2041-1723. (Nature Publishing Group)
Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in ppm concns. The existing technol. to remove these radioactive noble gases is a costly cryogenic distn.; alternatively, porous materials such as metal-org. frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal-org. frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtVSlu7zL&md5=707c333c8eb651e3cd510eb456b5f617
15
Schnobrich, J. K.; Lebel, O.; Cychosz, K. A.; Dailly, A.; Wong-Foy, A. G.; Matzger, A. J. Linker-Directed Vertex Desymmetrization for the Production of Coordination Polymers with High Porosity. J. Am. Chem. Soc. 2010, 132, 13941– 13948, DOI: 10.1021/ja107423k
[ACS Full Text ], [CAS], Google Scholar
15
Linker-Directed Vertex Desymmetrization for the Production of Coordination Polymers with High Porosity
Schnobrich, Jennifer K.; Lebel, Olivier; Cychosz, Katie A.; Dailly, Anne; Wong-Foy, Antek G.; Matzger, Adam J.
Journal of the American Chemical Society (2010), 132 (39), 13941-13948CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
Several noninterpenetrated microporous coordination polymers (MCPs) are derived by vertex desymmetrization using linkers with symmetry inequivalent coordinating groups, and these MCPs include properties such as rare metal clusters, new network topologies, and supramol. isomerism. Gas sorption in polymorphic frameworks, UMCM-152 and UMCM-153 (based upon a Cu-coordinated tetracarboxylated triphenylbenzene linker), reveals nearly identical properties with BET surface areas at 3300-3500 m2/g and excess H uptake of 5.7 and 5.8% at 77 K. In contrast, adsorption of organosulfur compds. dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (DMDBT) shows remarkably different capacities, providing direct evidence that liq.-phase adsorption is not solely dependent on surface area or linker/metal cluster identity. Structural features present in MCPs derived from these reduced symmetry linkers include the presence of more than one type of Cu-paddlewheel in a structure derived from a terphenyl tricarboxylate (UMCM-151) and a three-bladed Zn paddlewheel metal cluster in an MCP derived from a pentacarboxylated triphenylbenzene linker (UMCM-154).
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFKmt7fJ&md5=6df71c877714d682bf6abcff77920e9c
16
Moghadam, P. Z.; Islamoglu, T.; Goswami, S.; Exley, J.; Fantham, M.; Kaminski, C. F.; Snurr, R. Q.; Farha, O. K.; Fairen-Jimenez, D. Computer-aided discovery of a metal–organic framework with superior oxygen uptake. Nat. Commun. 2018, 9, 1378, DOI: 10.1038/s41467-018-03892-8
[Crossref], [PubMed], [CAS], Google Scholar
16
Computer-aided discovery of a metal-organic framework with superior oxygen uptake
Moghadam Peyman Z; Fantham Marcus; Kaminski Clemens F; Fairen-Jimenez David; Islamoglu Timur; Goswami Subhadip; Farha Omar K; Exley Jason; Snurr Randall Q; Farha Omar K; Farha Omar K
Nature communications (2018), 9 (1), 1378 ISSN:.
Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MjhsFSmuw%253D%253D&md5=1b73eac548f4efca88ba8e47f0eaa1c1
17
Sturluson, A.; Huynh, M. T.; Kaija, A. R.; Laird, C.; Yoon, S.; Hou, F.; Feng, Z.; Wilmer, C. E.; Colón, Y. J.; Chung, Y. G.; Siderius, D. W.; Simon, C. M. The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation. Mol. Simul. 2019, 45, 1082– 1121, DOI: 10.1080/08927022.2019.1648809
[Crossref], [CAS], Google Scholar
17
The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation†
Sturluson, Arni; Huynh, Melanie T.; Kaija, Alec R.; Laird, Caleb; Yoon, Sunghyun; Hou, Feier; Feng, Zhenxing; Wilmer, Christopher E.; Colon, Yamil J.; Chung, Yongchul G.; Siderius, Daniel W.; Simon, Cory M.
Molecular Simulation (2019), 45 (14-15), 1082-1121CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)
A review. Metal-org. frameworks (MOFs) are highly tuneable, extended-network, cryst., nanoporous materials with applications in gas storage, sepns., and sensing. We review how mol. models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chem. warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable mol. simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhsFChurjJ&md5=d02e6ff3468030ef2f7196f97a3ae863
18
Boyd, P. G.; Lee, Y.; Smit, B. Computational development of the nanoporous materials genome. Nat. Rev. Mater. 2017, 2, 17037, DOI: 10.1038/natrevmats.2017.37
[Crossref], [CAS], Google Scholar
18
Computational development of the nanoporous materials genome
Boyd, Peter G.; Lee, Yongjin; Smit, Berend
Nature Reviews Materials (2017), 2 (2), 17037CODEN: NRMADL; ISSN:2058-8437. (Nature Publishing Group)
A review. There is currently a push towards big data and data mining in materials research to accelerate discovery. Zeolites, metal-org. frameworks and other related cryst. porous materials are not immune to this phenomenon, as evidenced by the proliferation of porous structure databases and computational gas-adsorption screening studies over the past decade. The endeavour to identify the best materials for various gas sepn. and storage applications has led not only to thousands of synthesized structures, but also to the development of algorithms for building hypothetical materials. The materials databases assembled with these algorithms contain a much wider range of complex pore structures than have been synthesized, with the reasoning being that we have discovered only a small fraction of realizable structures and expanding upon these will accelerate rational design. In this Review, we highlight the methods developed to build these databases, and some of the important outcomes from large-scale computational screening studies.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtFegt7bI&md5=9c113afa97107e12fa266a20143d5627
19
Mancuso, J. L.; Mroz, A. M.; Le, K. N.; Hendon, C. H. Electronic Structure Modeling of Metal–Organic Frameworks. Chem. Rev. 2020, 120, 8641, DOI: 10.1021/acs.chemrev.0c00148
[ACS Full Text ], [CAS], Google Scholar
19
Electronic Structure Modeling of Metal-Organic Frameworks
Mancuso, JennaL.; Mroz, Austin M.; Le, Khoa N.; Hendon, Christopher H.
Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8641-8715CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. Owing to their mol. building blocks, yet highly cryst. nature, metal-org. frameworks (MOFs) sit at the interface between mol. and material. Their diverse structures and compns. enable them to be useful materials as catalysts in heterogeneous reactions, elec. conductors in energy storage and transfer applications, chromophores in photoenabled chem. transformations, and beyond. In all cases, d. functional theory (DFT) and higher-level methods for electronic structure detn. provide valuable quant. information about the electronic properties that underpin the functions of these frameworks. However, there are only two general modeling approaches in conventional electronic structure software packages: those that treat materials as extended, periodic solids, and those that treat materials as discrete mols. Each approach has features and benefits; both have been widely employed to understand the emergent chem. that arises from the formation of the metal-org. interface. This Review canvases these approaches to date, with emphasis placed on the application of electronic structure theory to explore reactivity and electron transfer using periodic, mol., and embedded models. This includes (i) computational chem. considerations such as how functional, k-grid, and other model variables are selected to enable insights into MOF properties, (ii) extended solid models that treat MOFs as materials rather than mols., (iii) the mechanics of cluster extn. and subsequent chem. enabled by these mol. models, (iv) catalytic studies using both solids and clusters thereof, and (v) embedded, mixed-method approaches, which simulate a fraction of the material using one level of theory and the remainder of the material using another dissimilar theor. implementation.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlymurvP&md5=2776969588b29b0185b24eede1f5e87a
20
Tan, J.-C.; Civalleri, B.; Erba, A.; Albanese, E. Quantum mechanical predictions to elucidate the anisotropic elastic properties of zeolitic imidazolate frameworks: ZIF-4 vs. ZIF-zni. CrystEngComm 2015, 17, 375– 382, DOI: 10.1039/C4CE01564A
[Crossref], [CAS], Google Scholar
20
Quantum mechanical predictions to elucidate the anisotropic elastic properties of zeolitic imidazolate frameworks: ZIF-4 vs. ZIF-zni
Tan, Jin-Chong; Civalleri, Bartolomeo; Erba, Alessandro; Albanese, Elisa
CrystEngComm (2015), 17 (2), 375-382CODEN: CRECF4; ISSN:1466-8033. (Royal Society of Chemistry)
We use ab initio d. functional theory (DFT) to elucidate the mech. properties of two topol. distinct zeolitic imidazolate framework (ZIF) materials: ZIF-4 and ZIF-zni, both of which have the same chem. compn. of Zn(Im)2 [Im = C3H3N2-] and are constructed from an identical Zn-Im-Zn basic building block. The CRYSTAL code was used to compute the single-crystal elastic consts. Cij of the (orthorhombic) ZIF-4 and (tetragonal) ZIF-zni structures at the PBE level of theory. Through tensorial anal. of the Cij, we reveal the three-dimensional representation surfaces of the Young's modulus, shear modulus, Poisson's ratio and linear compressibility, which enable us to describe the detailed elasticity behavior and to pinpoint basic crystal structure-property correlations. Notably, we discover that ZIF-4 can potentially exhibit a neg. Poisson's ratio, thereby representing the first example of an 'auxetic-ZIF' to be identified to date. Furthermore, we show that our DFT predictions are consistent with recently reported exptl. measurements of the Young's and bulk moduli of such complex ZIF structures.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVCjtLbN&md5=2efbd43f987a1e0271ff079702b0ec31
21
Ryder, M. R.; Maul, J.; Civalleri, B.; Erba, A. Quasi-Harmonic Lattice Dynamics of a Prototypical Metal–Organic Framework. Adv. Theory Simulations 2019, 2, 1900093, DOI: 10.1002/adts.201900093
[Crossref], [CAS], Google Scholar
21
Quasi-Harmonic Lattice Dynamics of a Prototypical Metal-Organic Framework
Ryder, Matthew R.; Maul, Jefferson; Civalleri, Bartolomeo; Erba, Alessandro
Advanced Theory and Simulations (2019), 2 (11), 1900093CODEN: ATSDCW; ISSN:2513-0390. (Wiley-VCH Verlag GmbH & Co. KGaA)
Quasi-harmonic lattice-dynamical calcns. are performed to investigate the combined effect of temp. and pressure on the structural and mech. properties of a prototypical metal-org. framework material: MOF-5. The softening upon compression of an A2g phonon mode at the Γ point in the high-symmetry Fm3m structure is identified, which leads to a symmetry redn. and a group-subgroup phase transition to a low-symmetry Fm3 phase for compressions larger than 0.8%. The effect of the symmetry redn. on the equation-of-state of MOF-5 is investigated, which provides a static bulk modulus K reducing from 17 to 14 GPa and a corresponding change of K' (pressure deriv. of K) from pos. to neg. The effect of pressure on the neg. thermal expansion of the framework and on its mech. response is analyzed. The evolution of the mech. anisotropy of MOF-5 as a function of pressure is also detd., which allows identifying the occurrence of a shear-induced mech. instability at 0.45 GPa.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitlyjsbvP&md5=0a8ccfdd89deed22ec740a7eaf2900f0
22
Bernales, V.; Ortuño, M. A.; Truhlar, D. G.; Cramer, C. J.; Gagliardi, L. Computational Design of Functionalized Metal–Organic Framework Nodes for Catalysis. ACS Cent. Sci. 2018, 4, 5– 19, DOI: 10.1021/acscentsci.7b00500
[ACS Full Text ], [CAS], Google Scholar
22
Computational Design of Functionalized Metal-Organic Framework Nodes for Catalysis
Bernales, Varinia; Ortuno, Manuel A.; Truhlar, Donald G.; Cramer, Christopher J.; Gagliardi, Laura
ACS Central Science (2018), 4 (1), 5-19CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
A review; recent progress in the synthesis and characterization of metal-org. frameworks (MOFs) has opened the door to an increasing no. of possible catalytic applications. The great versatility of MOFs creates a large chem. space, whose thorough exptl. examn. becomes practically impossible. Therefore, computational modeling is a key tool to support, rationalize, and guide exptl. efforts. In this outlook we survey the main methodologies employed to model MOFs for catalysis, and we review selected recent studies on the functionalization of their nodes. We pay special attention to catalytic applications involving natural gas conversion.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXitVShtLfN&md5=f706f2bdf686fc3334f1bc63a07290d7
23
Rosen, A. S.; Notestein, J. M.; Snurr, R. Q. Identifying promising metal–organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory. J. Comput. Chem. 2019, 40, 1305, DOI: 10.1002/jcc.25787
[Crossref], [PubMed], [CAS], Google Scholar
23
Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory
Rosen, Andrew S.; Notestein, Justin M.; Snurr, Randall Q.
Journal of Computational Chemistry (2019), 40 (12), 1305-1318CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
Metal-org. frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chem. compn. and topol. Due to their tunable nature, high-throughput computational screening is a particularly appealing method to reduce the time-to-discovery of MOFs with desirable phys. and chem. properties. In this work, a fully automated, high-throughput periodic d. functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof-of-concept, we use the high-throughput workflow to screen MOFs contg. open metal sites (OMSs) from the Computation-Ready, Exptl. MOF database for the oxidative C-H bond activation of methane. The results from the screening process suggest that, despite the strong C-H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXisVWktr0%253D&md5=13c289f2e38b866b0ab5b7687c40a8d1
24
Lee, K.; Howe, J. D.; Lin, L. C.; Smit, B.; Neaton, J. B. Small-Molecule Adsorption in Open-Site Metal-Organic Frameworks: A Systematic Density Functional Theory Study for Rational Design. Chem. Mater. 2015, 27, 668– 678, DOI: 10.1021/cm502760q
[ACS Full Text ], [CAS], Google Scholar
24
Small-Molecule Adsorption in Open-Site Metal-Organic Frameworks: A Systematic Density Functional Theory Study for Rational Design
Lee, Kyuho; Howe, Joshua D.; Lin, Li-Chiang; Smit, Berend; Neaton, Jeffrey B.
Chemistry of Materials (2015), 27 (3), 668-678CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
Using d. functional theory, the authors systematically computed and investigated the binding enthalpies of 14 different small mols. in a series of isostructural metal-org. frameworks, M-MOF-74, with M = Mg, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn. The small mols. considered include major flue-gas components, trace gases, and small hydrocarbons, i.e., H2, CO, CO2, H2O, H2S, N2, NH3, SO2, CH4, C2H2, C2H4, C2H6, C3H6, and C3H8. In total, the adsorption energetics of 140 unique systems are presented and discussed. Dispersion interactions were included by employing a non-local van der Waals d. functional, vdW-DF2. Hubbard U corrections were applied to the localized d electrons of transition metal atoms, and the impact of such corrections was assessed quant. For systems for which measured binding enthalpies have been reported, these calcns. lead to excellent overall agreement with exptl. detd. structures and isosteric heats of adsorption. For systems that have yet to be realized or characterized, this study provides quant. predictions, establishes a better understanding of the role of different transition-metal cations in small-mol. binding at open-metal sites, and identifies routes for predicting potential candidates for energy-related gas-sepn. applications. For example, the authors predict that Cu-MOF-74 will exhibit selectivity of CO2 over H2O and that Mn-MOF-74 can be used to sep. trace flue-gas impurities and toxic gases from gas mixts.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFOku7vM&md5=d07ba6dc8fae92cd042217e73d1ed78d
25
Odoh, S. O.; Cramer, C. J.; Truhlar, D. G.; Gagliardi, L. Quantum-Chemical Characterization of the Properties and Reactivities of Metal–Organic Frameworks. Chem. Rev. 2015, 115, 6051– 6111, DOI: 10.1021/cr500551h
[ACS Full Text ], [CAS], Google Scholar
25
Quantum-Chemical Characterization of the Properties and Reactivities of Metal-Organic Frameworks
Odoh, Samuel O.; Cramer, Christopher J.; Truhlar, Donald G.; Gagliardi, Laura
Chemical Reviews (Washington, DC, United States) (2015), 115 (12), 6051-6111CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. The following topic are discussed: Design and potential uses of MOFs; Electronic structure methods (Hartree-Fock, MP2, CC, CASSCF, DFT including various functionals, TDDFT, periodic DFT and DFT+U, combined Quantum-mech. and Mol.-mech. methods); Properties of MOFs; Gas adsorption and sepn.; Catalysis and reactivity (oxidn., hydrogenation, and Knoevenagel condensation reactions).
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXmsFyis7w%253D&md5=ca28570cc0e94eb3c784747f5b6060df
26
Frenkel, D.; Smit, B. Understanding Molecular Simulations: from Algorithms to Applications, 2nd ed.; Academic Press: San Diego, 2002.
[Crossref], Google Scholar
There is no corresponding record for this reference.
27
Smit, B.; Maesen, T. L. M. Molecular Simulations of Zeolites: Adsorption, Diffusion, and Shape Selectivity. Chem. Rev. 2008, 108, 4125– 4184, DOI: 10.1021/cr8002642
[ACS Full Text ], [CAS], Google Scholar
27
Molecular Simulations of Zeolites: Adsorption, Diffusion, and Shape Selectivity
Smit, Berend; Maesen, Theo L. M.
Chemical Reviews (Washington, DC, United States) (2008), 108 (10), 4125-4184CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. Details of simulation studies for adsorption, diffusion, and shape selectivity on zeolites have been reviewed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFKlurrL&md5=7a607f8f328c57fb1c88a004d4cf04da
28
Gropp, C.; Canossa, S.; Wuttke, S.; Gándara, F.; Li, Q.; Gagliardi, L.; Yaghi, O. M. Standard Practices of Reticular Chemistry. ACS Cent. Sci. 2020, 6, 1255, DOI: 10.1021/acscentsci.0c00592
[ACS Full Text ], [CAS], Google Scholar
28
Standard Practices of Reticular Chemistry
Gropp, Cornelius; Canossa, Stefano; Wuttke, Stefan; Gandara, Felipe; Li, Qiaowei; Gagliardi, Laura; Yaghi, Omar M.
ACS Central Science (2020), 6 (8), 1255-1273CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
A review. Since 1995 when the first of metal-org. frameworks was crystd. with the strong bond approach, where metal ions are joined by charged org. linkers exemplified by carboxylates, followed by proof of their porosity in 1998 and ultrahigh porosity in 1999, a revolution in the development of their chem. has ensued. This is being reinforced by the discovery of two- and three-dimensional covalent org. frameworks in 2005 and 2007. Currently, the chem. of such porous, cryst. frameworks is collectively referred to as reticular chem., which is being practiced in over 100 countries. The involvement of researchers from various backgrounds and fields, and the vast scope of this chem. and its societal applications, necessitate articulating the "Std. Practices of Reticular Chem.". Reticular chem. is a growing field of science with a multitude of practitioners with diverse frames of thinking, making the need for std. practices and quality indicators ever more compelling.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlans7%252FI&md5=d5842bd4eab4542bb6a405ffdaa33fc3
29
The Cambridge Structural Database. ccdc.cam.ac.uk/solutions/csd-system/components/csd (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
30
Shevchenko, A. P.; Eremin, R. A.; Blatov, V. A. The CSD and knowledge databases: from answers to questions. CrystEngComm 2020, in press. DOI: 10.1039/D0CE00265H
[Crossref], [PubMed], Google Scholar
There is no corresponding record for this reference.
31
Van Heest, T.; Teich-McGoldrick, S. L.; Greathouse, J. A.; Allendorf, M. D.; Sholl, D. S. Identification of metal-organic framework materials for adsorption separation of rare gases: Applicability of ideal adsorbed solution theory (IAST) and effects of inaccessible framework regions. J. Phys. Chem. C 2012, 116, 13183– 13195, DOI: 10.1021/jp302808j
[ACS Full Text ], [CAS], Google Scholar
31
Identification of Metal-Organic Framework Materials for Adsorption Separation of Rare Gases: Applicability of Ideal Adsorbed Solution Theory (IAST) and Effects of Inaccessible Framework Regions
Van Heest, Timothy; Teich-McGoldrick, Stephanie L.; Greathouse, Jeffery A.; Allendorf, Mark D.; Sholl, David S.
Journal of Physical Chemistry C (2012), 116 (24), 13183-13195CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
A collection of >3000 MOFs with exptl. confirmed structures were screened for performance in three binary sepns.: Ar/Kr, Kr/Xe, and Xe/Rn. 70 materials were selected for further anal., and calcns. were performed to account for inaccessible regions. Single component GCMC calcns. were performed to parametrize IAST calcns. on these 70 materials. An approach that avoids possible imprecision in IAST due to curve-fitting of single component isotherms is introduced. The precision of IAST for these gas pairs was confirmed with extensive binary GCMC calcns. For each binary sepn., materials were identified with predicted performance that surpasses the state of the art. A significant no. of materials are reverse selective in the sense that a smaller gas species is preferably adsorbed over a larger species. The phys. origin of this phenomenon is explained. The effect of temp. on sepn. performance was also examd.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XnsVKlurY%253D&md5=57e20f1fe778adb9f3382dc54284ee6e
32
Watanabe, T.; Sholl, D. S. Accelerating Applications of Metal–Organic Frameworks for Gas Adsorption and Separation by Computational Screening of Materials. Langmuir 2012, 28, 14114– 14128, DOI: 10.1021/la301915s
[ACS Full Text ], [CAS], Google Scholar
32
Accelerating Applications of Metal-Organic Frameworks for Gas Adsorption and Separation by Computational Screening of Materials
Watanabe, Taku; Sholl, David S.
Langmuir (2012), 28 (40), 14114-14128CODEN: LANGD5; ISSN:0743-7463. (American Chemical Society)
The selection of metal-org. frameworks (MOFs) for gas adsorption and sepn. has become a significant challenge over the past decade because of the large no. of new structures reported every year. We applied a multiscale computational approach to screen existing MOFs for CO2/N2 sepn. Pore characteristics of 1163 MOFs were analyzed by the method developed by Haldoupis, Nair, and Sholl (Haldoupis, E.; Nair, S.; Sholl, D. S. J. Am. Chem. Soc.2010, 132, 7528) using a simple steric model. On the basis of the pore size anal., 359 MOFs were examd. by classical mol. simulations. Adsorption and diffusion properties were computed using grand canonical Monte Carlo (GCMC) and mol. dynamics (MD) simulations, resp. These mol. simulations were used to assess which materials hold the greatest promise as membrane materials for CO2/N2 sepns. Finally, d. functional theory (DFT) calcns. were performed to provide preliminary information on the dynamic framework motion of selected MOFs.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVSmurfE&md5=cf6a8db16f92e64ef59a297af92ee0cf
33
Goldsmith, J.; Wong-Foy, A. G.; Cafarella, M. J.; Siegel, D. J. Theoretical Limits of Hydrogen Storage in Metal–Organic Frameworks: Opportunities and Trade-Offs. Chem. Mater. 2013, 25, 3373– 3382, DOI: 10.1021/cm401978e
[ACS Full Text ], [CAS], Google Scholar
33
Theoretical Limits of Hydrogen Storage in Metal-Organic Frameworks: Opportunities and Trade-Offs
Goldsmith, Jacob; Wong-Foy, Antek G.; Cafarella, Michael J.; Siegel, Donald J.
Chemistry of Materials (2013), 25 (16), 3373-3382CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
Because of their high surface areas, crystallinity, and tunable properties, metal-org. frameworks (MOFs) have attracted interest as next-generation materials for gas capture and storage. While much effort was devoted to the discovery of new MOFs, a vast catalog of existing MOFs resides within the Cambridge Structural Database (CSD), many of whose gas uptake properties have not been assessed. Here the authors employ data mining and automated structure anal. to identify, cleanup, and rapidly predict the H storage properties of these compds. Approx. 20,000 candidate compds. were generated from the CSD using an algorithm that removes solvent/guest mols. These compds. were then characterized with respect to their surface area and porosity. Employing the empirical relation between excess H2 uptake and surface area, the authors predict the theor. total H storage capacity for the subset of ∼4000 compds. exhibiting nontrivial internal porosity. The screening identifies several overlooked compds. having high theor. capacities; these compds. are suggested as targets of opportunity for addnl. exptl. characterization. More importantly, screening reveals that the relation between gravimetric and volumetric H2 d. is concave downward, with maximal volumetric performance occurring for surface areas of 3100-4800 m2/g. H2 storage in MOFs will not benefit from further improvements in surface area alone. Rather, discovery efforts should aim to achieve moderate mass densities and surface areas simultaneously, while ensuring framework stability upon solvent removal.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFOqtLjO&md5=b1e813cea5e39d4b1c7760c20ff32f2e
34
Chung, Y. G.; Camp, J.; Haranczyk, M.; Sikora, B. J.; Bury, W.; Krungleviciute, V.; Yildirim, T.; Farha, O. K.; Sholl, D. S.; Snurr, R. Q. Computation-ready, experimental metal-organic frameworks: a tool to enable high-throughput screening of nanoporous crystals. Chem. Mater. 2014, 26, 6185– 6192, DOI: 10.1021/cm502594j
[ACS Full Text ], [CAS], Google Scholar
34
Computation-Ready, Experimental Metal-Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals
Chung, Yongchul G.; Camp, Jeffrey; Haranczyk, Maciej; Sikora, Benjamin J.; Bury, Wojciech; Krungleviciute, Vaiva; Yildirim, Taner; Farha, Omar K.; Sholl, David S.; Snurr, Randall Q.
Chemistry of Materials (2014), 26 (21), 6185-6192CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
Exptl. refined crystal structures for metal-org. frameworks (MOFs) often include solvent mols. and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, the authors have constructed a database of MOF structures that are derived from exptl. data but are immediately suitable for mol. simulations. The computation-ready, exptl. (CoRE) MOF database contains over 4700 porous structures with publically available at. coordinates. Important phys. and chem. properties including the surface area and pore dimensions are reported for these structures. To demonstrate the utility of the database, the authors performed grand canonical Monte Carlo simulations of methane adsorption on all structures in the CoRE MOF database. The authors studied the structural properties of the CoRE MOFs that govern methane storage capacity and found that these relations agree well with those derived recently from a large database of hypothetical MOFs.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Oiur7E&md5=3ad2adec61ab717772baf1380e04cf7a
35
Nazarian, D.; Camp, J. S.; Sholl, D. S. A Comprehensive Set of High-Quality Point Charges for Simulations of Metal–Organic Frameworks. Chem. Mater. 2016, 28, 785– 793, DOI: 10.1021/acs.chemmater.5b03836
[ACS Full Text ], [CAS], Google Scholar
35
A Comprehensive Set of High-Quality Point Charges for Simulations of Metal-Organic Frameworks
Nazarian, Dalar; Camp, Jeffrey S.; Sholl, David S.
Chemistry of Materials (2016), 28 (3), 785-793CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
Most classical simulations of metal-org. frameworks model electrostatic interactions using point charges on each atom in the structure. We report at. point charges derived from periodic d. functional theory (DFT) electronic structure calcns. for more than 2000 unique exptl. synthesized metal-org. frameworks (MOFs). These charges are publicly available as a supplement to the Computation-Ready Exptl. MOF database. These DFT-derived at. point charges are compared to semiempirical group contribution and charge equilibration methods for assigning charges. As an example of using these charges, we examd. each MOF for usefulness in the adsorptive removal of tert-Bu mercaptan (TBM) from natural gas. Monte Carlo simulations revealed many candidate MOF structures with high selectivity for TBM over CH4 and high TBM capacity. We anticipate that this public data set of at. point charges for MOFs will facilitate high-throughput screening for a wide variety of applications in which electrostatic interactions must be considered.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XjvFersw%253D%253D&md5=44bb2616d70ad59ffdd726f4af9dcd3d
36
Nazarian, D.; Camp, J. S.; Chung, Y. G.; Snurr, R. Q.; Sholl, D. S. Large-scale refinement of metal-organic framework structures using density Functional Theory. Chem. Mater. 2017, 29, 2521– 2528, DOI: 10.1021/acs.chemmater.6b04226
[ACS Full Text ], [CAS], Google Scholar
36
Large-Scale Refinement of Metal-Organic Framework Structures Using Density Functional Theory
Nazarian, Dalar; Camp, Jeffrey S.; Chung, Yongchul G.; Snurr, Randall Q.; Sholl, David S.
Chemistry of Materials (2017), 29 (6), 2521-2528CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
Efforts to computationally characterize large nos. of nanoporous materials often rely on databases of exptl. resolved crystal structures. The accuracy of exptl. crystal structures used in such calcns. has a significant impact on the reliability of the results. In this work, we report structures optimized using periodic d. functional theory (DFT) for more than 800 exptl. synthesized metal-org. frameworks (MOFs). Many MOFs changed significantly upon structural optimization, particularly materials that were crystallog. resolved in their solvated form. For each MOF, we simulated the adsorption of CH4 and CO2 using grand canonical Monte Carlo both before and after DFT optimization. The DFT optimization has a large impact on simulated gas adsorption in some cases - for example, CO2 loading at 1 bar changed by more than 25% in over 25% of the MOFs we considered.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVGqsbzE&md5=1e92027e1b8257e1dac60409d975a717
37
Ongari, D.; Boyd, P. G.; Kadioglu, O.; Mace, A. K.; Keskin, S.; Smit, B. Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials. J. Chem. Theory Comput. 2019, 15, 382– 401, DOI: 10.1021/acs.jctc.8b00669
[ACS Full Text ], [CAS], Google Scholar
37
Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials
Ongari, Daniele; Boyd, Peter G.; Kadioglu, Ozge; Mace, Amber K.; Keskin, Seda; Smit, Berend
Journal of Chemical Theory and Computation (2019), 15 (1), 382-401CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
Charge equilibration (Qeq) methods can est. the electrostatic potential of mols. and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute d. functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar mols. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in metal-org. frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality DFT-derived DDEC charges for 2338 MOF structures. We focused on the systematic errors that are attributable to specific atom types to quantify the final precision that one can expect from Qeq methods in the context of gas adsorption where the electrostatic potential plays a significant role, namely, CO2 and H2S adsorption. In conclusion, both the type of algorithm and the input parameters have a large impact on the resulting charges, and we draw some guidelines to help the user to choose the proper combination of the two for obtaining a meaningful set of charges. We show that, considering this set of MOFs, the accuracy of the original Qeq scheme is often still comparable with the most recent variants, even if it clearly fails in the presence of certain atom types, such as alkali metals.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXitFKnu7%252FE&md5=b681aaba638f7f133a157d2df13e7aa9
38
Qiao, Z.; Zhang, K.; Jiang, J. In silico screening of 4764 computation-ready, experimental metal–organic frameworks for CO 2 separation. J. Mater. Chem. A 2016, 4, 2105– 2114, DOI: 10.1039/C5TA08984K
[Crossref], [CAS], Google Scholar
38
In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation
Qiao, Zhiwei; Zhang, Kang; Jiang, Jianwen
Journal of Materials Chemistry A: Materials for Energy and Sustainability (2016), 4 (6), 2105-2114CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
We report a mol. simulation study to screen 4764 computation-ready, exptl. metal-org. frameworks (CoRE-MOFs) for CO2 sepn. from flue gas (CO2/N2) and natural gas (CO2/CH4). Quant. relationships are established, for the first time, between the metal type and adsorbent evaluation criteria (adsorption selectivity and capacity, working capacity and regenerability). It is found that alkalis exist in 75% of alkali-MOFs as nonframework ions or open metal sites, and 75% of alk.-MOFs contain alkalines as open metal sites; thus alkali- and alk.-MOFs exhibit high adsorption selectivity and large capacity. Combining selectivity, working capacity and regenerability, however, alkali- and alk.-MOFs possess the lowest performance for CO2 sepn. Among ∼1000 lanthanide-based CoRE-MOFs, 50% contain lanthanides as open metal sites and have the highest performance. The best 30 CoRE-MOFs are identified for CO2/N2 and CO2/CH4 sepn., and they mostly contain lanthanides. Furthermore, we predict the breakthrough curves in two identified CoRE-MOFs and demonstrate their superior sepn. performance. This modeling study highlights the central importance of adsorbent evaluation by holistic criteria, and suggests that lanthanides could be interesting metals in the design of new MOFs for CO2 sepn.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVCltbjI&md5=729fc33df7b0e0d675eb68f03a7b9797
39
Erdös, M.; de Lange, M. F.; Kapteijn, F.; Moultos, O. A.; Vlugt, T. J. H. In Silico Screening of Metal–Organic Frameworks for Adsorption-Driven Heat Pumps and Chillers. ACS Appl. Mater. Interfaces 2018, 10, 27074– 27087, DOI: 10.1021/acsami.8b09343
[ACS Full Text ], [CAS], Google Scholar
39
In Silico Screening of Metal-Organic Frameworks for Adsorption-Driven Heat Pumps and Chillers
Erdos, Mate; de Lange, Martijn F.; Kapteijn, Freek; Moultos, Othonas A.; Vlugt, Thijs J. H.
ACS Applied Materials & Interfaces (2018), 10 (32), 27074-27087CODEN: AAMICK; ISSN:1944-8244. (American Chemical Society)
A computational screening of 2930 exptl. synthesized metal-org. frameworks (MOFs) is carried out to find the best-performing structures for adsorption-driven cooling (AC) applications with methanol and ethanol as working fluids. The screening methodol. consists of four subsequent screening steps for each adsorbate. At the end of each step, the most promising MOFs for AC application are selected for further investigation. In the first step, the structures are selected on the basis of phys. properties (pore limiting diam.). In each following step, points of the adsorption isotherms of the selected structures are calcd. from Monte Carlo simulations in the grand-canonical ensemble. The most promising MOFs are selected on the basis of the working capacity of the structures and the location of the adsorption step (if present), which can be related to the applicable operational conditions in AC. Because of the possibility of reversible pore condensation (first-order phase transition), the mid-d. scheme is used to efficiently and accurately det. the location of the adsorption step. At the end of the screening procedure, six MOFs with high deliverable working capacities (∼0.6 mL working fluid in 1 mL structure) and diverse adsorption step locations are selected for both adsorbates from the original 2930 structures. Because the highest exptl. measured deliverable working capacity to date for MOFs with methanol is ca. 0.45 mL mL-1, the selected six structures show the potential to improve the efficiency of ACs.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlGit77F&md5=632a4d7b307be7d619db2d679daf6ce2
40
Altintas, C.; Avci, G.; Daglar, H.; Nemati Vesali Azar, A.; Erucar, I.; Velioglu, S.; Keskin, S. An extensive comparative analysis of two MOF databases: high-throughput screening of computation-ready MOFs for CH 4 and H 2 adsorption. J. Mater. Chem. A 2019, 7, 9593– 9608, DOI: 10.1039/C9TA01378D
[Crossref], [CAS], Google Scholar
40
An extensive comparative analysis of two MOF databases: high-throughput screening of computation-ready MOFs for CH4 and H2 adsorption
Altintas, Cigdem; Avci, Gokay; Daglar, Hilal; Nemati Vesali Azar, Ayda; Erucar, Ilknur; Velioglu, Sadiye; Keskin, Seda
Journal of Materials Chemistry A: Materials for Energy and Sustainability (2019), 7 (16), 9593-9608CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
Computation-ready metal-org. framework (MOF) databases (DBs) have tremendous value since they provide directly useable crystal structures for mol. simulations. The currently available two DBs, the CoRE DB (computation-ready, exptl. MOF database) and CSDSS DB (Cambridge Structural Database non-disordered MOF subset) have been widely used in high-throughput mol. simulations. These DBs were constructed using different methods for collecting MOFs, removing bound and unbound solvents, treating charge balancing ions, missing hydrogens and disordered atoms of MOFs. As a result of these methodol. differences, some MOFs were reported under the same name but with different structural features in the two DBs. In this work, we first identified 3490 common MOFs of CoRE and CSDSS DBs and then performed mol. simulations to compute their CH4 and H2 uptakes. We found that 387 MOFs result in different gas uptakes depending on from which DB their structures were taken and we identified them as 'problematic' MOFs. CH4/H2 mixt. adsorption simulations showed that adsorbent performances of problematic MOFs, such as selectivity and regenerability, also significantly change depending on the DB used and lead to large variations in the ranking of materials and identification of the top MOFs. Possible reasons of different structure modifications made by the two DBs were investigated in detail for problematic MOFs. We described five main cases to categorize the problematic MOFs and discussed what types of different modifications were performed by the two DBs in terms of removal of unbound and bound solvents, treatment of missing hydrogen atoms, charge balancing ions etc. with several examples in each case. With this categorization, we aimed to direct researchers to computation-ready MOFs that are the most consistent with their exptl. reported structures. We also provided the new computation-ready structures for 54 MOFs for which the correct structures were missing in both DBs. This extensive comparative anal. of the two DBs will clearly show how and why the DBs differently modified the same MOFs and guide the users to choose either of the computation-ready MOFs from the two DBs depending on their purpose of mol. simulations.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXlslelt70%253D&md5=9d918838e0fd5203b96e6ab969f22b24
41
Li, A.; Bueno-Perez, R.; Wiggin, S.; Fairen-Jimenez, D. Enabling efficient exploration of metal–organic frameworks in the Cambridge Structural Database. CrystEngComm 2020, in press. DOI: 10.1039/D0CE00299B
[Crossref], [PubMed], Google Scholar
There is no corresponding record for this reference.
42
Barthel, S.; Alexandrov, E. V.; Proserpio, D. M.; Smit, B. Distinguishing Metal–Organic Frameworks. Cryst. Growth Des. 2018, 18, 1738– 1747, DOI: 10.1021/acs.cgd.7b01663
[ACS Full Text ], [CAS], Google Scholar
42
Distinguishing Metal-Organic Frameworks
Barthel, Senja; Alexandrov, Eugeny V.; Proserpio, Davide M.; Smit, Berend
Crystal Growth & Design (2018), 18 (3), 1738-1747CODEN: CGDEFU; ISSN:1528-7483. (American Chemical Society)
We consider two metal-org. frameworks as identical if they share the same bond network respecting the atom types. An algorithm is presented that decides whether two metal-org. frameworks are the same. It is based on distinguishing structures by comparing a set of descriptors that is obtained from the bond network. We demonstrate our algorithm by analyzing the CoRe MOF database of DFT optimized structures with DDEC partial at. charges using the program package ToposPro.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhslyqtrY%253D&md5=ad3b3610b1f238eea55aa9303bd2fa06
43
Chen, T.; Manz, T. A. Identifying misbonded atoms in the 2019 CoRE metal–organic framework database. RSC Adv. 2020, 10, 26944– 26951, DOI: 10.1039/D0RA02498H
[Crossref], [CAS], Google Scholar
43
Identifying misbonded atoms in the 2019 CoRE metal-organic framework database
Chen, Taoyi; Manz, Thomas A.
RSC Advances (2020), 10 (45), 26944-26951CODEN: RSCACL; ISSN:2046-2069. (Royal Society of Chemistry)
Databases of exptl.-derived metal-org. framework (MOF) crystal structures are useful for large-scale computational screening to identify which MOFs are best-suited for particular applications. However, these crystal structures must be cleaned to identify and/or correct various artifacts. Herein, further cleaning of the 2019 CoRE MOF database is performed to identify structures with misbonded or isolated atoms: (i) structures contg. an isolated atom, (ii) structures contg. atoms too close together (i.e., overlapping atoms), (iii) structures contg. a misplaced hydrogen atom, (iv) structures contg. an under-bonded carbon atom (which might be caused by missing hydrogen atoms), and (v) structures contg. an over-bonded carbon atom. This study should not be viewed as the final cleaning of this database, but rather as progress along the way towards the goal of someday achieving a completely cleaned set of exptl.-derived MOF crystal structures. We performed atom typing for all of the accepted structures to identify those structures that can be parameterized by previously reported forcefield precursors (Chen and Manz, RSC Adv., 2019, 9, 36492-36507). We report several forcefield precursors (e.g., net at. charges, atom-in-material polarizabilities, atom-in-material dispersion coeffs., electron cloud parameters, etc.) for more than five thousand MOFs in the 2019 CoRE MOF database.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhsVSrurrN&md5=5a6580741ead58cdc762224cbda4ecf3
44
Wilkinson, M. D. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 2016, 3, 160018, DOI: 10.1038/sdata.2016.18
[Crossref], [PubMed], [CAS], Google Scholar
44
The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson Mark D; Dumontier Michel; Aalbersberg I Jsbrand Jan; Appleton Gabrielle; Dumon Olivier; Groth Paul; Strawn George; Axton Myles; Baak Arie; Blomberg Niklas; Boiten Jan-Willem; da Silva Santos Luiz Bonino; Bourne Philip E; Bouwman Jildau; Brookes Anthony J; Clark Tim; Crosas Merce; Dillo Ingrid; Edmunds Scott; Evelo Chris T; Finkers Richard; Gonzalez-Beltran Alejandra; Rocca-Serra Philippe; Sansone Susanna-Assunta; Gray Alasdair J G; Goble Carole; Grethe Jeffrey S; Heringa Jaap; Kok Ruben; 't Hoen Peter A C; Hooft Rob; Kuhn Tobias; Kok Joost; Lusher Scott J; Mons Barend; Martone Maryann E; Mons Albert; Packer Abel L; Persson Bengt; Roos Marco; Thompson Mark; van Schaik Rene; Schultes Erik; Sengstag Thierry; Slater Ted; Swertz Morris A; van der Lei Johan; van Mulligen Erik; Mons Barend; Velterop Jan; Waagmeester Andra; Wittenburg Peter; Wolstencroft Katherine; Zhao Jun; Mons Barend
Scientific data (2016), 3 (), 160018 ISSN:.
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28bjslyrtQ%253D%253D&md5=e4ce8cf366db2280e54eb0168940720b
45
Coudert, F. Materials Databases: The Need for Open, Interoperable Databases with Standardized Data and Rich Metadata. Adv. Theory Simulations 2019, 2, 1900131, DOI: 10.1002/adts.201900131
[Crossref], Google Scholar
There is no corresponding record for this reference.
46
Ma, T.; Kapustin, E. A.; Yin, S. X.; Liang, L.; Zhou, Z.; Niu, J.; Li, L.-H.; Wang, Y.; Su, J.; Li, J.; Wang, X.; Wang, W. D.; Wang, W.; Sun, J.; Yaghi, O. M. Single-crystal x-ray diffraction structures of covalent organic frameworks. Science 2018, 361, 48– 52, DOI: 10.1126/science.aat7679
[Crossref], [PubMed], [CAS], Google Scholar
46
Single-crystal x-ray diffraction structures of covalent organic frameworks
Ma, Tianqiong; Kapustin, Eugene A.; Yin, Shawn X.; Liang, Lin; Zhou, Zhengyang; Niu, Jing; Li, Li-Hua; Wang, Yingying; Su, Jie; Li, Jian; Wang, Xiaoge; Wang, Wei David; Wang, Wei; Sun, Junliang; Yaghi, Omar M.
Science (Washington, DC, United States) (2018), 361 (6397), 48-52CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
A review. The crystn. problem is an outstanding challenge in the chem. of porous covalent org. frameworks (COFs). Their structural characterization was limited to modeling and solns. based on powder x-ray or electron diffraction data. Single crystals of COFs amenable to x-ray diffraction characterization were not reported. A general procedure was developed to grow large single crystals of 3-dimensional imine-based COFs (COF-300, hydrated form of COF-300, COF-303, LZU-79, and LZU-111). The high quality of the crystals allowed collection of single-crystal x-ray diffraction data of up to 0.83-Å resoln., leading to unambiguous soln. and precise anisotropic refinement. Characteristics such as degree of interpenetration, arrangement of H2O guests, the reversed imine connectivity, linker disorder, and uncommon topol. were deciphered with at. precision-aspects impossible to det. without single crystals.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1Cjs7zM&md5=9c25f3d95459d93a6affbfb36fef477c
47
Tong, M.; Lan, Y.; Qin, Z.; Zhong, C. Computation-ready, experimental covalent organic framework for methane delivery: screening and material design. J. Phys. Chem. C 2018, 122, 13009– 13016, DOI: 10.1021/acs.jpcc.8b04742
[ACS Full Text ], [CAS], Google Scholar
47
Computation-Ready, Experimental Covalent Organic Framework for Methane Delivery: Screening and Material Design
Tong, Minman; Lan, Youshi; Qin, Zhenglong; Zhong, Chongli
Journal of Physical Chemistry C (2018), 122 (24), 13009-13016CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
CH4 storage assocd. with adsorbed natural gas technol. attracts considerable researches on finding porous materials with remarkable CH4 delivery performance. In this work, we update the online accessible computation-ready, exptl. (CoRE) covalent org. frameworks (COFs) database with 280 COFs in 12 topologies. All framework structures are constructed and compiled from the resp. exptl. studies and are further evaluated for CH4 delivery. The highest deliverable capacity (DC) between 65 and 5.8 bar among the CoRE COFs is 190 v(STP)/v at 298 K achieved by 3D PI-COF-4. Structure-property relationships show that large volumetric surface area generally benefits CH4 delivery. 2D-COFs can also be top performing materials if constructing their pore channels is passable in three dimensions, as the volumetric surface area will be increased accordingly. This idea can be realized by enlarging the interlayer spacings of 2D-COFs. We also evaluate the DC of CoRE COFs under conditions of 233 K, 65 bar (storage) and 358 K, 5.8 bar (discharge). The highest DC obtained from the CoRE COFs and the designed 2D-COFs are 314 and 337 v(STP)/v, resp.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtVeis7vP&md5=e77a3db672ab59db2e8b1547ed94f4e4
48
Pizzi, G.; Cepellotti, A.; Sabatini, R.; Marzari, N.; Kozinsky, B. AiiDA: automated interactive infrastructure and database for computational science. Comput. Mater. Sci. 2016, 111, 218– 230, DOI: 10.1016/j.commatsci.2015.09.013
[Crossref], Google Scholar
There is no corresponding record for this reference.
49
Huber, S. P. AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance. Sci. Data 2020, 7, 300, DOI: 10.1038/s41597-020-00638-4
[Crossref], [PubMed], [CAS], Google Scholar
49
AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance
Huber Sebastiaan P; Zoupanos Spyros; Uhrin Martin; Talirz Leopold; Kahle Leonid; Hauselmann Rico; Yakutovich Aliaksandr V; Andersen Casper W; Ramirez Francisco F; Adorf Carl S; Gargiulo Fernando; Kumbhar Snehal; Passaro Elsa; Johnston Conrad; Cepellotti Andrea; Mounet Nicolas; Marzari Nicola; Pizzi Giovanni; Huber Sebastiaan P; Zoupanos Spyros; Uhrin Martin; Talirz Leopold; Kahle Leonid; Hauselmann Rico; Yakutovich Aliaksandr V; Andersen Casper W; Ramirez Francisco F; Adorf Carl S; Gargiulo Fernando; Kumbhar Snehal; Passaro Elsa; Johnston Conrad; Cepellotti Andrea; Mounet Nicolas; Marzari Nicola; Pizzi Giovanni; Talirz Leopold; Yakutovich Aliaksandr V; Gresch Dominik; Muller Tiziano; Merkys Andrius; Kozinsky Boris; Kozinsky Boris
Scientific data (2020), 7 (1), 300 ISSN:.
The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38blvFyksw%253D%253D&md5=89f4a5f6d6a831f029c8cc9f2b2b3246
50
CURATED covalent organic frameworks database. materialscloud.org/discover/curated-cofs (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
51
Altundal, O. F.; Altintas, C.; Keskin, S. Can COFs replace MOFs in flue gas separation? high-throughput computational screening of COFs for CO 2 /N 2 separation. J. Mater. Chem. A 2020, 8, 14609, DOI: 10.1039/D0TA04574H
[Crossref], [CAS], Google Scholar
51
Can COFs replace MOFs in flue gas separation? high-throughput computational screening of COFs for CO2/N2 separation
Altundal, Omer Faruk; Altintas, Cigdem; Keskin, Seda
Journal of Materials Chemistry A: Materials for Energy and Sustainability (2020), 8 (29), 14609-14623CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
Covalent org. frameworks (COFs) are under study as adsorbent and membrane candidates for gas sepn. applications. However, exptl. testing of all synthesized COF materials as adsorbents and membranes under different operating conditions is not practical. Herein, the authors used a high-throughput computational screening approach to study adsorption- and membrane-based flue gas sepn. performances of 295 COFs. Adsorption selectivity, working capacity, percent regenerability and adsorbent performance score of COFs were calcd. for sepn. of CO2/N2 mixt. for 3 different cyclic adsorption processes, pressure swing adsorption (PSA), vacuum swing adsorption (VSA) and temp. swing adsorption (TSA). The top performing COFs were identified for each process based on the combination of several metrics. Selectivities of the top COFs were predicted to be greater than those of zeolites and activated carbons. Mol. simulations were performed considering the wet flue gas for the top COF adsorbents and results revealed that most COFs retained their high CO2 selectivities in the presence of H2O. Using COFs with detailed geometry optimization and high-accuracy partial charges in mol. simulations led to lower selectivities and adsorbent performance scores compared to using exptl. reported COFs with approx. charges. Membrane-based flue gas sepn. performances of COFs were also studied and most COFs have comparable CO2 permeabilities with metal org. frameworks (MOFs), up to 3.96 × 106 barrer, however their membrane selectivities were lower than MOFs, 0.38-21, due to their large pores and the lack of metal sites in their frameworks. Structure-performance relations revealed that among the COFs the authors studied, the ones with pore sizes <10 Å, accessible surface areas <4500 m2 g-1 and 0.6 < porosity <0.8 are not only highly selective adsorbents but also CO2 selective membranes.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlynurrM&md5=1322ca870eb69a5b8918f8f26afc3b1f
52
Lan, Y.; Han, X.; Tong, M.; Huang, H.; Yang, Q.; Liu, D.; Zhao, X.; Zhong, C. Materials genomics methods for high-throughput construction of COFs and targeted synthesis. Nat. Commun. 2018, 9, 1– 10, DOI: 10.1038/s41467-018-07720-x
[Crossref], [PubMed], [CAS], Google Scholar
52
Two high-risk susceptibility loci at 6p25.3 and 14q32.13 for Waldenstrom macroglobulinemia
McMaster, Mary L.; Berndt, Sonja I.; Zhang, Jianqing; Slager, Susan L.; Li, Shengchao Alfred; Vajdic, Claire M.; Smedby, Karin E.; Yan, Huihuang; Birmann, Brenda M.; Brown, Elizabeth E.; Smith, Alex; Kleinstern, Geffen; Fansler, Mervin M.; Mayr, Christine; Zhu, Bin; Chung, Charles C.; Park, Ju-Hyun; Burdette, Laurie; Hicks, Belynda D.; Hutchinson, Amy; Teras, Lauren R.; Adami, Hans-Olov; Bracci, Paige M.; McKay, James; Monnereau, Alain; Link, Brian K.; Vermeulen, Roel C. H.; Ansell, Stephen M.; Maria, Ann; Diver, W. Ryan; Melbye, Mads; Ojesina, Akinyemi I.; Kraft, Peter; Boffetta, Paolo; Clavel, Jacqueline; Giovannucci, Edward; Besson, Caroline M.; Canzian, Federico; Travis, Ruth C.; Vineis, Paolo; Weiderpass, Elisabete; Montalvan, Rebecca; Wang, Zhaoming; Yeager, Meredith; Becker, Nikolaus; Benavente, Yolanda; Brennan, Paul; Foretova, Lenka; Maynadie, Marc; Nieters, Alexandra; de Sanjose, Silvia; Staines, Anthony; Conde, Lucia; Riby, Jacques; Glimelius, Bengt; Hjalgrim, Henrik; Pradhan, Nisha; Feldman, Andrew L.; Novak, Anne J.; Lawrence, Charles; Bassig, Bryan A.; Lan, Qing; Zheng, Tongzhang; North, Kari E.; Tinker, Lesley F.; Cozen, Wendy; Severson, Richard K.; Hofmann, Jonathan N.; Zhang, Yawei; Jackson, Rebecca D.; Morton, Lindsay M.; Purdue, Mark P.; Chatterjee, Nilanjan; Offit, Kenneth; Cerhan, James R.; Chanock, Stephen J.; Rothman, Nathaniel; Vijai, Joseph; Goldin, Lynn R.; Skibola, Christine F.; Caporaso, Neil E.
Nature Communications (2018), 9 (1), 1-12CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
Waldenstrom macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a rare, chronic B-cell lymphoma with high heritability. We conduct a two-stage genome-wide assocn. study of WM/LPL in 530 unrelated cases and 4362 controls of European ancestry and identify two high-risk loci assocd. with WM/LPL at 6p25.3 (rs116446171, near EXOC2 and IRF4; OR = 21.14, 95% CI: 14.40-31.03, P = 1.36 × 10-54) and 14q32.13 (rs117410836, near TCL1; OR = 4.90, 95% CI: 3.45-6.96, P = 8.75 × 10-19). Both risk alleles are obsd. at a low frequency among controls (∼2-3%) and occur in excess in affected cases within families. In silico data suggest that rs116446171 may have functional importance, and in functional studies, we demonstrate increased reporter transcription and proliferation in cells transduced with the 6p25.3 risk allele. Although further studies are needed to fully elucidate underlying biol. mechanisms, together these loci explain 4% of the familial risk and provide insights into genetic susceptibility to this malignancy.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvFGqurbP&md5=34353fe6721d80f7d73498ca40046eb8
53
Jablonka, K. M.; Ongari, D.; Moosavi, S. M.; Smit, B. Big-Data Science in Porous Materials: Materials Genomics and Machine Learning. Chem. Rev. 2020, 120, 8066, DOI: 10.1021/acs.chemrev.0c00004
[ACS Full Text ], [CAS], Google Scholar
53
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
Jablonka, Kevin Maik; Ongari, Daniele; Moosavi, Seyed Mohamad; Smit, Berend
Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8066-8129CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. By combining metal nodes with org. linkers we can potentially synthesize millions of possible metal-org. frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too many materials to be processed using conventional, brute force, methods. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We show how to select appropriate training sets, survey approaches that are used to represent these materials in feature space, and review different learning architectures, as well as evaluation and interpretation strategies. In the second part, we review how the different approaches of machine learning have been applied to porous materials. In particular, we discuss applications in the field of gas storage and sepn., the stability of these materials, their electronic properties, and their synthesis. Given the increasing interest of the scientific community in machine learning, we expect this list to rapidly expand in the coming years.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFWjsLnL&md5=e6ec07cd45585938f549be18b31fbf19
54
Moosavi, S. M.; Nandy, A.; Jablonka, K. M.; Ongari, D.; Janet, J. P.; Boyd, P. G.; Lee, Y.; Smit, B.; Kulik, H. J. Understanding the diversity of the metal-organic framework ecosystem. Nat. Commun. 2020, 11, 4068, DOI: 10.1038/s41467-020-17755-8
[Crossref], [PubMed], [CAS], Google Scholar
54
Understanding the diversity of the metal-organic framework ecosystem
Moosavi, Seyed Mohamad; Nandy, Aditya; Jablonka, Kevin Maik; Ongari, Daniele; Janet, Jon Paul; Boyd, Peter G.; Lee, Yongjin; Smit, Berend; Kulik, Heather J.
Nature Communications (2020), 11 (1), 4068CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
Abstr.: Millions of distinct metal-org. frameworks (MOFs) can be made by combining metal nodes and org. linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new exptl. or predicted structure adds new information. For MOF chemists, the chem. design space is a combination of pore geometry, metal nodes, org. linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chem. design space. In this work, we develop a machine learning method to quantify similarities of MOFs to analyze their chem. diversity. This diversity anal. identifies biases in the databases, and we show that such bias can lead to incorrect conclusions. The developed formalism in this study provides a simple and practical guideline to see whether new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhs1WrsbfE&md5=d9ba7ae4ec44a4716746a8a21b2edf0d
55
Jablonka, K. M.; Ongari, D.; Smit, B. Applicability of tail corrections in the molecular simulations of porous materials. J. Chem. Theory Comput. 2019, 15, 5635– 5641, DOI: 10.1021/acs.jctc.9b00586
[ACS Full Text ], [CAS], Google Scholar
55
Applicability of Tail Corrections in the Molecular Simulations of Porous Materials
Jablonka, Kevin Maik; Ongari, Daniele; Smit, Berend
Journal of Chemical Theory and Computation (2019), 15 (10), 5635-5641CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
Mol. simulations with periodic boundary conditions require the definition of a certain cutoff radius, rc, beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases the use of tail corrections is well-established, which can remedy this truncation of the potential. These corrections are built under the assumption that beyond rc the radial distribution function, g(r), is equal to one. In this work we shed some light on the discussion of whether tail corrections should be used in the modeling of heterogeneous systems. We show that for the adsorption of gases in a diverse set of nanoporous cryst. materials (zeolites, covalent org. frameworks, and metal-org. frameworks), tail corrections are a convenient choice to make the adsorption results less sensitive to the details of the truncation.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1egu7vJ&md5=0894aa136f8cdedb769a0677b84681a3
56
Yang, Q.; Liu, D.; Zhong, C.; Li, J.-R. Development of Computational Methodologies for Metal–Organic Frameworks and Their Application in Gas Separations. Chem. Rev. 2013, 113, 8261– 8323, DOI: 10.1021/cr400005f
[ACS Full Text ], [CAS], Google Scholar
56
Development of Computational Methodologies for Metal-Organic Frameworks and Their Application in Gas Separations
Yang, Qingyuan; Liu, Dahuan; Zhong, Chongli; Li, Jian-Rong
Chemical Reviews (Washington, DC, United States) (2013), 113 (10), 8261-8323CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
A review. The authors devote the attention to highlighting both the successes and the limitations of various computational methodologies for metal org. frameworks. As an illustration, the authors provide a state of-the-art review on modeling studies of gas sepns. in MOFs using these new methods and concepts. Since the newly developed computational methodologies are normally used in combination with the conventional ones, for the sake of continuity and clarity, some of the conventional methods that have been widely adopted in MOF studies are also briefly discussed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVKit7bL&md5=0265edb5dc95d324cc20367290c8507c
57
Hamad, S.; Balestra, S. R.; Bueno-Perez, R.; Calero, S.; Ruiz-Salvador, A. R. Atomic charges for modeling metal-organic frameworks: Why and how. J. Solid State Chem. 2015, 223, 144– 151, DOI: 10.1016/j.jssc.2014.08.004
[Crossref], [CAS], Google Scholar
57
Atomic charges for modeling metal-organic frameworks: Why and how
Hamad, Said; Balestra, Salvador R. G.; Bueno-Perez, Rocio; Calero, Sofia; Ruiz-Salvador, A. Rabdel
Journal of Solid State Chemistry (2015), 223 (), 144-151CODEN: JSSCBI; ISSN:0022-4596. (Elsevier B.V.)
Atomic partial charges are parameters of key importance in the simulation of Metal-Org. Frameworks (MOFs), since Coulombic interactions decrease with the distance more slowly than van der Waals interactions. But despite its relevance, there is no method to unambiguously assign charges to each atom, since at. charges are not quantum observables. There are several methods that allow the calcn. of at. charges, most of them starting from the electronic wavefunction or the electronic d. or the system, as obtained with quantum mechanics calcns. In this work, we describe the most common methods employed to calc. at. charges in MOFs. In order to show the influence that even small variations of structure have on at. charges, we present the results that we obtained for DMOF-1. We also discuss the effect that small variations of at. charges have on the predicted structural properties of IRMOF-1.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVCjtr7K&md5=ac51e68b7f8c6171978011121e75fac2
58
Mayo, S. L.; Olafson, B. D.; Goddard, W. a. DREIDING: a generic force field for molecular simulations. J. Phys. Chem. 1990, 94, 8897– 8909, DOI: 10.1021/j100389a010
[ACS Full Text ], [CAS], Google Scholar
58
DREIDING: a generic force field for molecular simulations
Mayo, Stephen L.; Olafson, Barry D.; Goddard, William A., III
Journal of Physical Chemistry (1990), 94 (26), 8897-909CODEN: JPCHAX; ISSN:0022-3654.
The parameters are given for a new generic force field, DREIDING, that is useful for predicting structures and dynamics of org., biol., and main-group inorg. mols. The philosophy in DREIDING is to use general force consts. and geometry parameters based on simple hybridization considerations rather than individual force consts. and geometric parameters that depend on the particular combination of atoms involved in the bond, angle, or torsion terms. Thus all bond distances are derived from at. radii, and there is only one force const. each for bonds, angles, and inversions and only six different values for torsional barriers. Parameters are defined for all possible combinations of atoms and new atoms can be added to the force field rather simply. The parameters are given for the "nonmetallic" main-group elements (B, C, N, O, F columns for the C, Si, Ge, and Sn rows) plus H and a few metals (Na, Ca, Zn, Fe). The accuracy of the DREIDING force field is tested by comparing with (i) 76 accurately detd. crystal structures of org. compds. involving H, C, N, O, F, P, S, Cl, and Br, (ii) rotational barriers of a no. of mols., and (iii) relative conformational energies and barriers of a no. of mols. There is excellent agreement.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXmtlyhtL0%253D&md5=c2b2e75dedb934f18bad57d15d8944d4
59
Rappe, A. K.; Casewit, C. J.; Colwell, K. S.; Goddard, W. a.; Skiff, W. M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 1992, 114, 10024– 10035, DOI: 10.1021/ja00051a040
[ACS Full Text ], [CAS], Google Scholar
59
UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations
Rappe, A. K.; Casewit, C. J.; Colwell, K. S.; Goddard, W. A., III; Skiff, W. M.
Journal of the American Chemical Society (1992), 114 (25), 10024-35CODEN: JACSAT; ISSN:0002-7863.
A new mol. mechanics force field, the Universal force field (UFF), is described wherein the force field parameters are estd. using general rules based only on the element, its hybridization and its connectivity. The force field functional forms, parameters, and generating formulas for the full periodic table are presented.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK38Xmtl2qur8%253D&md5=cf41e8bb9ad299fd5d79f070d690afe1
60
Potoff, J. J.; Siepmann, J. I. Vapor-liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen. AIChE J. 2001, 47, 1676– 1682, DOI: 10.1002/aic.690470719
[Crossref], [CAS], Google Scholar
60
Vapor-liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen
Potoff, Jeffrey J.; Siepmann, J. Ilja
AIChE Journal (2001), 47 (7), 1676-1682CODEN: AICEAC; ISSN:0001-1541. (American Institute of Chemical Engineers)
New force fields for carbon dioxide and nitrogen are introduced that quant. reproduce the vapor-liq. equil. (VLE) of the neat systems and their mixts. with alkanes. In addn. to the usual VLE calcns. for pure CO2 and N2, calcns. of the binary mixts. with propane were used in the force-field development to achieve a good balance between dispersive and electrostatic (quadrupole-quadrupole) interactions. The transferability of the force fields was then assessed from calcns. of the VLE for the binary mixts. with n-hexane, the binary mixt. of CO2/N2, and the ternary mixt. of CO2/N2/propane. The VLE calcns. were carried out using configurational-bias Monte Carlo simulations in either the grand canonical ensemble with histogram-reweighting or in the Gibbs ensemble.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXlsVCrt78%253D&md5=ad43c62adf3f96989c660eeff73b73e2
61
Awesome Materials Informatics. github.com/tilde-lab/awesome-materials-informatics (accessed on July 2020).
Google Scholar
There is no corresponding record for this reference.
62
Jain, A.; Ong, S. P.; Chen, W.; Medasani, B.; Qu, X.; Kocher, M.; Brafman, M.; Petretto, G.; Rignanese, G.-M.; Hautier, G.; Gunter, D.; Persson, K. A. FireWorks: a dynamic workflow system designed for high-throughput applications. Concurr. Comput. Pract. Exp. 2015, 27, 5037– 5059, DOI: 10.1002/cpe.3505
[Crossref], Google Scholar
There is no corresponding record for this reference.
63
Curtarolo, S.; Setyawan, W.; Hart, G. L.; Jahnatek, M.; Chepulskii, R. V.; Taylor, R. H.; Wang, S.; Xue, J.; Yang, K.; Levy, O.; Mehl, M. J.; Stokes, H. T.; Demchenko, D. O.; Morgan, D. AFLOW: An automatic framework for high-throughput materials discovery. Comput. Mater. Sci. 2012, 58, 218– 226, DOI: 10.1016/j.commatsci.2012.02.005
[Crossref], [CAS], Google Scholar
63
AFLOW: An automatic framework for high-throughput materials discovery
Curtarolo, Stefano; Setyawan, Wahyu; Hart, Gus L. W.; Jahnatek, Michal; Chepulskii, Roman V.; Taylor, Richard H.; Wang, Shidong; Xue, Junkai; Yang, Kesong; Levy, Ohad; Mehl, Michael J.; Stokes, Harold T.; Demchenko, Denis O.; Morgan, Dane
Computational Materials Science (2012), 58 (), 218-226CODEN: CMMSEM; ISSN:0927-0256. (Elsevier B.V.)
Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compds. and metastable structures, electronic structure, surface, and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present Aflow (Automatic Flow), a software framework for high-throughput calcn. of crystal structure properties of alloys, intermetallics and inorg. compds. The Aflow software is available for the scientific community on the website of the materials research consortium, aflowlib.org. Its geometric and electronic structure anal. and manipulation tools are addnl. available for online operation at the same website. The combination of automatic methods and user online interfaces provide a powerful tool for efficient quantum computational materials discovery and characterization.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktL8%253D&md5=8129bab53c054672274b0d6fa64172ef
64
Adorf, C. S.; Dodd, P. M.; Ramasubramani, V.; Glotzer, S. C. Simple data and workflow management with the signac framework. Comput. Mater. Sci. 2018, 146, 220– 229, DOI: 10.1016/j.commatsci.2018.01.035
[Crossref], Google Scholar
There is no corresponding record for this reference.
65
Simon, C. M.; Braun, E.; Carraro, C.; Smit, B. Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, E287– E296, DOI: 10.1073/pnas.1613874114
[Crossref], [PubMed], [CAS], Google Scholar
65
Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties
Simon, Cory M.; Braun, Efrem; Carraro, Carlo; Smit, Berend
Proceedings of the National Academy of Sciences of the United States of America (2017), 114 (3), E287-E296CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
Some nanoporous, cryst. materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest mols., which qual. impacts adsorption behavior. The authors pose and solve a statistical mech. model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest mols. incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. The model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and sepns., chem. sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXitlWltQ%253D%253D&md5=e49d7e160f19f212ee4c62b67a1a1099
66
Haranczyk, M.; Sethian, J. A. Automatic structure analysis in high-throughput characterization of porous materials. J. Chem. Theory Comput. 2010, 6, 3472– 3480, DOI: 10.1021/ct100433z
[ACS Full Text ], [CAS], Google Scholar
66
Automatic Structure Analysis in High-Throughput Characterization of Porous Materials
Haranczyk, Maciej; Sethian, James A.
Journal of Chemical Theory and Computation (2010), 6 (11), 3472-3480CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
Inspection of the structure and the void space of a porous material is a crit. step in most computational studies involving guest mols. Some sections of the void space, like inaccessible pockets, have to be identified and blocked in mol. simulations. These pockets are typically detected by visual anal. of the geometry, potential, or free energy landscapes, or a histogram of an initial mol. simulation. Such visual anal. is time-consuming and inhibits characterization of large sets of materials required in studies focused on identification of the best materials for a given application. An automatic approach is presented that bypasses manual visual anal. of this kind, thereby enabling execution of mol. simulations in an unsupervised, high-throughput manner. In the approach, a partial differential equations-based front propagation technique is used to segment out channels and inaccessible pockets of a periodic unit cell of a material. The problem is casted as a path planning problem in 3D space representing a periodic fragment of porous material, and solve the resulting Eikonal equation by using fast marching methods. One attractive feature of this approach is that the to-be-analyzed data can be of varying types, including, for example, a 3D grid representing the distance to the material's surface, the potential or free energy of a mol. inside the material, or even a histogram (a set of snapshots) from a mol. simulation showing areas which were visited by the mol. during the simulation.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht12jurnF&md5=35a2f75a1726480be59e513dd987e445
67
Fairen-Jimenez, D.; Moggach, S. A.; Wharmby, M. T.; Wright, P. A.; Parsons, S.; Düren, T. Opening the gate: Framework flexibility in ZIF-8 explored by experiments and simulations. J. Am. Chem. Soc. 2011, 133, 8900– 8902, DOI: 10.1021/ja202154j
[ACS Full Text ], [CAS], Google Scholar
67
Opening the Gate: Framework Flexibility in ZIF-8 Explored by Experiments and Simulations
Fairen-Jimenez, D.; Moggach, S. A.; Wharmby, M. T.; Wright, P. A.; Parsons, S.; Duren, T.
Journal of the American Chemical Society (2011), 133 (23), 8900-8902CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
ZIF-8 is a zeolitic imidazole-based metal-org. framework with large cavities interconnected by narrow windows. Because the small size of the windows, it allows in principle for mol. sieving of gases such as H2 and CH4. However, the unexpected adsorption of large mols. on ZIF-8 suggests the existence of structural flexibility. ZIF-8 flexibility is explored combining different exptl. techniques with mol. simulation. The ZIF-8 structure is modified by gas adsorption uptake in the same way as it is at a very high pressure (i.e., 14,700 bar) due to a swing effect in the imidazolate linkers, giving access to the porosity. Tuning the flexibility, and so the opening of the small windows, has a further impact on the design of advanced mol. sieving membrane materials for gas sepn., adjusting the access of fluids to the porous network.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmtlWrt70%253D&md5=f9d8904cd7cd4f8d703600d849849f8c
68
Kolokolov, D. I.; Stepanov, A. G.; Jobic, H. Mobility of the 2-Methylimidazolate Linkers in ZIF-8 Probed by 2H NMR: Saloon Doors for the Guests. J. Phys. Chem. C 2015, 119, 27512– 27520, DOI: 10.1021/acs.jpcc.5b09312
[ACS Full Text ], [CAS], Google Scholar
68
Mobility of the 2-Methylimidazolate Linkers in ZIF-8 Probed by 2H NMR: Saloon Doors for the Guests
Kolokolov, Daniil I.; Stepanov, Alexander G.; Jobic, Herve
Journal of Physical Chemistry C (2015), 119 (49), 27512-27520CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
ZIF-8 is one of the most interesting metal-org. frameworks due to its high stability and unique capabilities for hydrocarbons sepn. Its porous network is formed by large almost spherical cavities interconnected by very narrow windows, ∼3.4 Å, which should be too small even for methane. At the same time the direct exptl. observations show that ZIF-8 cavities are able to host even such large mols. as benzene. This effect is assocd. with the flexibility of the cavity widows, arising from dynamical freedom on the 2-methylimidazole (2-mIM) linkers that form the framework. In this work, by means of 2H NMR we show that the 2-mIM linkers of the ZIF-8 are very mobile and their mobility is sensitive to the presence of benzene guest. In contrast with other known MOFs based on linearly bonded carboxylates, in guest-free ZIF-8 the plane of 2-mIM linker exhibits two-site flips within a sector of 2φf = 34° with very low activation barrier (1.5 kJ mol-1) and high rates (∼1012 s-1). Above 380 K the linkers begin to demonstrate addnl. fast librations with gradually increasing amplitudes γlib comparable with the two-site flips (γlib = ±17° above 560 K). This is direct evidence that the ZIF-8 linkers twist notably, thus increasing the aperture of the windows sufficiently to fit very large mols. Upon benzene loading, the geometry of the obsd. motions remains similar but the potential barrier of the linkers flipping rises up to 9 kJ mol-1.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVOrtrrE&md5=b023e7e91500aec760a217e0a240d553
69
Mace, A.; Barthel, S.; Smit, B. Automated Multiscale Approach to Predict Self-Diffusion from a Potential Energy Field. J. Chem. Theory Comput. 2019, 15, 2127– 2141, DOI: 10.1021/acs.jctc.8b01255
[ACS Full Text ], [CAS], Google Scholar
69
Automated Multiscale Approach To Predict Self-Diffusion from a Potential Energy Field
Mace, Amber; Barthel, Senja; Smit, Berend
Journal of Chemical Theory and Computation (2019), 15 (4), 2127-2141CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
For large-scale screening studies there is a need to est. the diffusion of gas mols. in nanoporous materials more efficiently than (brute force) mol. dynamics. In particular for systems with low diffusion coeffs. mol. dynamics can be prohibitively expensive. An alternative is to compute the hopping rates between adsorption sites using transition state theory. For large-scale screening this requires the automatic detection of the transition states between the adsorption sites along the different diffusion paths. Here an algorithm is presented that analyzes energy grids for the moving particles. It detects the energies at which diffusion paths are formed, together with their directions. This allows for easy identification of nondiffusive systems. For diffusive systems, it partitions the grid coordinates assigned to energy basins and transitions states, permitting a transition state theory based anal. of the diffusion. We test our method on CH4 diffusion in zeolites, using a std. kinetic Monte Carlo simulation based on the output of our grid anal. We find that it is accurate, fast, and rigorous without limitations to the geometries of the diffusion tunnels or transition states.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXjvFCksrs%253D&md5=dc6cf6f5950882d172bf169a46b5e9a7
70
Kloutse, F. A.; Zacharia, R.; Cossement, D.; Chahine, R. Specific heat capacities of MOF-5, Cu-BTC, Fe-BTC, MOF-177 and MIL-53 (Al) over wide temperature ranges: Measurements and application of empirical group contribution method. Microporous Mesoporous Mater. 2015, 217, 1– 5, DOI: 10.1016/j.micromeso.2015.05.047
[Crossref], [CAS], Google Scholar
70
Specific heat capacities of MOF-5, Cu-BTC, Fe-BTC, MOF-177 and MIL-53 (Al) over wide temperature ranges: Measurements and application of empirical group contribution method
Kloutse, F. A.; Zacharia, R.; Cossement, D.; Chahine, R.
Microporous and Mesoporous Materials (2015), 217 (), 1-5CODEN: MIMMFJ; ISSN:1387-1811. (Elsevier B.V.)
Sp. heat capacities of five MOFs: MOF-5, Cu-BTC, Fe-BTC, MIL-53 (Al) and MOF-177 are reported over wide temp. ranges. For MOF-5, which is the primary candidate material down selected by the Hydrogen Storage Engineering Center of Excellence (HSECoE) for cryo-adsorptive vehicular hydrogen storage, sp. heat capacity in the range 2-300 K is obtained by combining the measurements using a Calvet calorimeter and a direct adiabatic relaxation calorimeter while for remaining MOFs, Cps are measured in the temp. range 80-320 K using the Calvet calorimeter alone. All MOFs exhibit monotonically increasing sp. heat capacities with no visible thermal anomalies implying the absence of any temp.-induced phase transitions in the temp. range considered. A simple ion-based group contribution approach is applied to empirically predict the sp. heat capacities of all MOFs at 323 K.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVeisbrK&md5=bc72b049a3f8c91b0aec309fb7dc2092
71
Kapil, V.; Wieme, J.; Vandenbrande, S.; Lamaire, A.; Van Speybroeck, V.; Ceriotti, M. Modeling the Structural and Thermal Properties of Loaded Metal–Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations. J. Chem. Theory Comput. 2019, 15, 3237– 3249, DOI: 10.1021/acs.jctc.8b01297
[ACS Full Text ], [CAS], Google Scholar
71
Modeling the Structural and Thermal Properties of Loaded Metal-Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations
Kapil, Venkat; Wieme, Jelle; Vandenbrande, Steven; Lamaire, Aran; Van Speybroeck, Veronique; Ceriotti, Michele
Journal of Chemical Theory and Computation (2019), 15 (5), 3237-3249CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
Metal-org. frameworks show both fundamental interest and great promise for applications in adsorption-based technologies, such as the sepn. and storage of gases. The flexibility and complexity of the mol. scaffold pose a considerable challenge to atomistic modeling, esp. when also considering the presence of guest mols. We investigate the role played by quantum and anharmonic fluctuations in the archetypical case of MOF-5, comparing the material at various levels of methane loading. Accurate path integral simulations of such effects are made affordable by the introduction of an accelerated simulation scheme and the use of an optimized force field based on first-principles ref. calcns. We find that the level of statistical treatment that is required for predictive modeling depends significantly on the property of interest. The thermal properties of the lattice are generally well described by a quantum harmonic treatment, with the adsorbate behaving in a classical but strongly anharmonic manner. The heat capacity of the loaded framework - which plays an important role in the characterization of the framework and in detg. its stability to thermal fluctuations during adsorption/desorption cycles - requires, however, a full quantum and anharmonic treatment, either by path integral methods or by a simple but approx. scheme. We also present mol.-level insight into the nanoscopic interactions contributing to the material's properties and suggest design principles to optimize them.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXnvFCgsL4%253D&md5=9e7fc9aa110cd247244ddec9f4a0fe8d
72
Moosavi, S. M.; Boyd, P. G.; Sarkisov, L.; Smit, B. Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids. ACS Cent. Sci. 2018, 4, 832– 839, DOI: 10.1021/acscentsci.8b00157
[ACS Full Text ], [CAS], Google Scholar
72
Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids
Moosavi, Seyed Mohamad; Boyd, Peter G.; Sarkisov, Lev; Smit, Berend
ACS Central Science (2018), 4 (7), 832-839CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
Metal-org. frameworks (MOFs) have emerged as versatile materials for applications ranging from gas sepn. and storage, catalysis, and sensing. The attractive feature of MOFs is that by changing the ligand and/or metal, they can be chem. tuned to perform optimally for a given application. In most, if not all, of these applications one also needs a material that has a sufficient mech. stability, but our understanding of how changes in the chem. structure influence mech. stability is limited. In this work, we rationalize how the mech. properties of MOFs are related to framework bonding topol. and ligand structure. We illustrate that the functional groups on the org. ligands can either enhance the mech. stability through formation of a secondary network of non-bonded interactions or soften the material by destabilizing the bonded network of a MOF. In addn., we show that synergistic effect of the bonding network of the material and the secondary network is required to achieve optimal mech. stability of a MOF. The developed mol. insights in this work can be used for systematic improvement of the mech. stability of the materials by careful selection of the functional groups.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFGntbvK&md5=781d4c266a29f4e5aff7ce762651aad5
73
Moghadam, P. Z.; Rogge, S. M.; Li, A.; Chow, C.-M.; Wieme, J.; Moharrami, N.; Aragones-Anglada, M.; Conduit, G.; Gomez-Gualdron, D. A.; Van Speybroeck, V.; Fairen-Jimenez, D. Structure-Mechanical Stability Relations of Metal-Organic Frameworks via Machine Learning. Matter 2019, 1, 219– 234, DOI: 10.1016/j.matt.2019.03.002
[Crossref], Google Scholar
There is no corresponding record for this reference.
74
Fumanal, M.; Capano, G.; Barthel, S.; Smit, B.; Tavernelli, I. Energy-based descriptors for photo-catalytically active metal–organic framework discovery. J. Mater. Chem. A 2020, 8, 4473– 4482, DOI: 10.1039/C9TA13506E
[Crossref], [CAS], Google Scholar
74
Energy-based descriptors for photo-catalytically active metal-organic framework discovery
Fumanal, Maria; Capano, Gloria; Barthel, Senja; Smit, Berend; Tavernelli, Ivano
Journal of Materials Chemistry A: Materials for Energy and Sustainability (2020), 8 (8), 4473-4482CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
Metal-org. frameworks (MOFs) consist of metal nodes that are connected by org. linkers. They are thus highly chem. tunable materials given the broad range of potential linkers and nodes that can be chosen for their synthesis. Their tunability has recently sparked interest in the development of new MOF photo-catalysts for energy-related applications such as hydrogen (H2) evolution and CO2 redn. The sheer no. of potentially synthesizable MOFs requires defining descriptors that allow prediction of their performance with this aim. Herein we propose a systematic computational protocol to det. two energy-based descriptors that are directly related to the performance of a MOF as a photocatalyst. These descriptors assess the UV-vis light absorption capability and the band energy alignment with respect to redox processes and/or co-catalyst energy levels. High-throughput screening based on cost-effective computations of these features is envisioned to aid the discovery of new promising photoactive systems.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXjvVKms7Y%253D&md5=4d782bebc3bee43259c67f396788d7b7
75
Gomez, D. A.; Toda, J.; Sastre, G. Screening of hypothetical metal–organic frameworks for H 2 storage. Phys. Chem. Chem. Phys. 2014, 16, 19001– 19010, DOI: 10.1039/C4CP01848F
[Crossref], [PubMed], [CAS], Google Scholar
75
Screening of hypothetical metal-organic frameworks for H2 storage
Gomez, Diego A.; Toda, Jordi; Sastre, German
Physical Chemistry Chemical Physics (2014), 16 (35), 19001-19010CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)
Computational screening throughout a database contg. ∼138,000 metal-org. frameworks (MOFs) was performed to select candidate structures for H storage. A total of 231 structures (of which 79 contain paddle-wheel units) have been selected that meet the gravimetric and volumetric targets at 100 atm and 77 K. Grand Canonical Monte Carlo simulations have been performed to calc. the isotherms and select structures which meet the targets at 50 atm, and also to check the adsorption in the low pressure regime (1 atm). From this a reduced set of 18 structures was analyzed in more detail, regarding not only gravimetric and volumetric uptake but also pore size distribution and pore vol. A few structures with 3% gravimetric uptake at 1 atm and 77 K perform at the best level found so far.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht1KktLvL&md5=6aae1bca7f853d87c92cfa64248224f7
76
Colón, Y. J.; Fairen-Jimenez, D.; Wilmer, C. E.; Snurr, R. Q. High-throughput screening of porous crystalline materials for hydrogen storage capacity near room temperature. J. Phys. Chem. C 2014, 118, 5383– 5389, DOI: 10.1021/jp4122326
[ACS Full Text ], [CAS], Google Scholar
76
High-Throughput Screening of Porous Crystalline Materials for Hydrogen Storage Capacity near Room Temperature
Colon, Yamil J.; Fairen-Jimenez, David; Wilmer, Christopher E.; Snurr, Randall Q.
Journal of Physical Chemistry C (2014), 118 (10), 5383-5389CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
The hydrogen storage capabilities of 18 383 porous cryst. structures possessing various degrees of Mg functionalization and diverse phys. properties were assessed through combined grand canonical Monte Carlo (GCMC) and quantum mech. approaches. GCMC simulations were performed for pressures of 2 and 100 bar at a temp. of 243 K. Abs. uptake at 100 bar and deliverable capacity between 100-2 bar were calcd. Maximum abs. and deliverable gravimetric capacities were 9.35 and 9.12 wt.%, resp. Volumetrically, abs. and deliverable capacities were 51 and 30 g/L, resp. The results reveal relations between hydrogen uptake and the phys. properties of the materials. It is shown that the introduction of an optimum amt. of magnesium alkoxide to increase the isosteric heat of adsorption is a promising strategy to improve hydrogen uptake and delivery near ambient temp.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXivFWisbY%253D&md5=7c668b77af1e4382069201bd704f6f53
77
Bobbitt, N. S.; Chen, J.; Snurr, R. Q. High-Throughput Screening of Metal-Organic Frameworks for Hydrogen Storage at Cryogenic Temperature. J. Phys. Chem. C 2016, 120, 27328– 27341, DOI: 10.1021/acs.jpcc.6b08729
[ACS Full Text ], [CAS], Google Scholar
77
High-Throughput Screening of Metal-Organic Frameworks for Hydrogen Storage at Cryogenic Temperature
Bobbitt, N. Scott; Chen, Jiayi; Snurr, Randall Q.
Journal of Physical Chemistry C (2016), 120 (48), 27328-27341CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
Metal-org. frameworks (MOFs) have attracted significant interest as a class of adsorbent materials for gas storage applications, including hydrogen storage for fuel cell vehicles. Here, we evaluated 137 953 hypothetical MOFs for hydrogen storage at cryogenic conditions (77 K) by detg. the deliverable storage capacity between 100 and 2 bar, using grand canonical Monte Carlo simulations. The highest predicted volumetric capacity for a structure in this study is 50 g/L, and the highest gravimetric capacity is almost 25 wt %. We find that the optimal void fraction is 0.9 and the optimal pore diam. is 12-15 Å. MOFs with larger pores have significant regions in the center of the pore with low hydrogen d., which lowers the storage efficiency. We give examples of MOFs with very large pores in which the hydrogen capacity can potentially be increased using catenation or functional groups to reduce the pore size and increase the surface area per vol. We also introduce a screening parameter, the binding fraction, which is the fraction of the unit cell vol. within a given distance of the framework. This metric is inexpensive to compute and is a strong predictor of hydrogen storage capacity. This simple parameter could be used to quickly screen even larger nos. of MOFs for gas adsorption capacity to identify the most promising candidates for more detailed study.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVaktr7N&md5=fd7b7f4d260d528da4c1044bcdd3c6ed
78
Thornton, A. W.; Simon, C. M.; Kim, J.; Kwon, O.; Deeg, K. S.; Konstas, K.; Pas, S. J.; Hill, M. R.; Winkler, D. A.; Haranczyk, M.; Smit, B. Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage. Chem. Mater. 2017, 29, 2844– 2854, DOI: 10.1021/acs.chemmater.6b04933
[ACS Full Text ], [CAS], Google Scholar
78
Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage
Thornton, Aaron W.; Simon, Cory M.; Kim, Jihan; Kwon, Ohmin; Deeg, Kathryn S.; Konstas, Kristina; Pas, Steven J.; Hill, Matthew R.; Winkler, David A.; Haranczyk, Maciej; Smit, Berend
Chemistry of Materials (2017), 29 (7), 2844-2854CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
The Materials Genome is in action: the mol. codes for millions of materials have been sequenced, predictive models have been developed, and now the challenge of hydrogen storage is targeted. Renewably generated hydrogen is an attractive transportation fuel with zero carbon emissions, but its storage remains a significant challenge. Nanoporous adsorbents have shown promising phys. adsorption of hydrogen approaching targeted capacities, but the scope of studies has remained limited. Here the Nanoporous Materials Genome, contg. over 850,000 materials, is analyzed with a variety of computational tools to explore the limits of hydrogen storage. Optimal features that maximize net capacity at room temp. include pore sizes of around 6 Å and void fractions of 0.1, while at cryogenic temps. pore sizes of 10 Å and void fractions of 0.5 are optimal. Our top candidates are found to be com. attractive as "cryo-adsorbents", with promising storage capacities at 77 K and 100 bar with 30% enhancement to 40 g/L, a promising alternative to liquefaction at 20 K and compression at 700 bar.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXjvVWhsr8%253D&md5=1f248dfa32a7542c24626d2f0990b241
79
Ahmed, A.; Seth, S.; Purewal, J.; Wong-Foy, A. G.; Veenstra, M.; Matzger, A. J.; Siegel, D. J. Exceptional hydrogen storage achieved by screening nearly half a million metal-organic frameworks. Nat. Commun. 2019, 10, 1568, DOI: 10.1038/s41467-019-09365-w
[Crossref], [PubMed], [CAS], Google Scholar
79
Exceptional hydrogen storage achieved by screening nearly half a million metal-organic frameworks
Ahmed Alauddin; Siegel Donald J; Seth Saona; Wong-Foy Antek G; Matzger Adam J; Purewal Justin; Veenstra Mike; Siegel Donald J; Siegel Donald J; Siegel Donald J
Nature communications (2019), 10 (1), 1568 ISSN:.
Few hydrogen adsorbents balance high usable volumetric and gravimetric capacities. Although metal-organic frameworks (MOFs) have recently demonstrated progress in closing this gap, the large number of MOFs has hindered the identification of optimal materials. Here, a systematic assessment of published databases of real and hypothetical MOFs is presented. Nearly 500,000 compounds were screened computationally, and the most promising were assessed experimentally. Three MOFs with capacities surpassing that of IRMOF-20, the record-holder for balanced hydrogen capacity, are demonstrated: SNU-70, UMCM-9, and PCN-610/NU-100. Analysis of trends reveals the existence of a volumetric ceiling at ∼40 g H2 L(-1). Surpassing this ceiling is proposed as a new capacity target for hydrogen adsorbents. Counter to earlier studies of total hydrogen uptake in MOFs, usable capacities in the highest-capacity materials are negatively correlated with density and volumetric surface area. Instead, capacity is maximized by increasing gravimetric surface area and porosity. This suggests that property/performance trends for total capacities may not translate to usable capacities.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M%252Fit1Ghsw%253D%253D&md5=26b8edf94cf43ba2819eb98f1bf873f6
80
Yazaydın, A. O.; Snurr, R. Q.; Park, T.-H.; Koh, K.; Liu, J.; LeVan, M. D.; Benin, A. I.; Jakubczak, P.; Lanuza, M.; Galloway, D. B.; Low, J. J.; Willis, R. R. Screening of Metal-Organic Frameworks for Carbon Dioxide Capture from Flue Gas Using a Combined Experimental and Modeling Approach. J. Am. Chem. Soc. 2009, 131, 18198– 18199, DOI: 10.1021/ja9057234
[ACS Full Text ], [CAS], Google Scholar
80
Screening of Metal-Organic Frameworks for Carbon Dioxide Capture from Flue Gas Using a Combined Experimental and Modeling Approach
Yazaydin, A. Ozgur; Snurr, Randall Q.; Park, Tae-Hong; Koh, Kyoungmoo; Liu, Jian; LeVan, M. Douglas; Benin, Annabelle I.; Jakubczak, Paulina; Lanuza, Mary; Galloway, Douglas B.; Low, John J.; Willis, Richard R.
Journal of the American Chemical Society (2009), 131 (51), 18198-18199CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
A diverse collection of 14 metal-org. frameworks (MOF) for flue gas CO2 capture are reported. Synthesis, characterization, and adsorption measurements for about half the MOF are reported; adsorption data were collected from the literature for the remaining MOF. The diversity of the selected materials will help improve the understanding fo MOF CO2 capture. Also, these data were used to validate a general strategy for mol. modeling of CO2 and other small mols. in MOF. This strategy is fully predicting with no parameter-fitting. This approach can be used to rapidly screen addnl. MOF, saving large amts. of exptl. time and costs. Grand canonical Monte Carlo simulations were performed for a model which included electrostatic and Lennard-Jones interactions among atoms in the system. The framework and individual CO2 mols. are considered to be rigid. Interactions among CO2 mols. were modeled with the TraAPPE force field (J.J. Potoff and J.I. Siepmann, 2001); Lennard-Jones parameters for MOF atoms were taken from DREIDING (S.L. Mayo, et al., 1990) and UFF (A.K. Rappe, et al., 1992) force fields. Partial charges on MOF atoms were derived from d. functional theory calcns.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFShsr7L&md5=ee067ec4cee9d1095897b19d957671db
81
Haldoupis, E.; Nair, S.; Sholl, D. S. Finding MOFs for highly selective CO 2/N 2 adsorption using materials screening based on efficient assignment of atomic point charges. J. Am. Chem. Soc. 2012, 134, 4313– 4323, DOI: 10.1021/ja2108239
[ACS Full Text ], [CAS], Google Scholar
81
Finding MOFs for Highly Selective CO2/N2 Adsorption Using Materials Screening Based on Efficient Assignment of Atomic Point Charges
Haldoupis, Emmanuel; Nair, Sankar; Sholl, David S.
Journal of the American Chemical Society (2012), 134 (9), 4313-4323CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
Electrostatic interactions are a crit. factor in the adsorption of quadrupolar species such as CO2 and N2 in metal-org. frameworks (MOFs) and other nanoporous materials. A version of the semiempirical charge equilibration method suitable for periodic materials can be used to efficiently assign charges and allow mol. simulations for a large no. of MOFs. This approach is illustrated by simulating CO2 and N2 adsorption in ∼500 MOFs; this is the largest set of structures for which this information was reported to date. For materials predicted by the calcns. to have promising adsorption selectivities, the authors performed more detailed calcns. in which accurate quantum chem. methods were used to assign at. point charges, and mol. simulations were used to assess mol. diffusivities and binary adsorption isotherms. The results identify two MOFs, exptl. known to be stable upon solvent removal, that are predicted to show no diffusion limitations for adsorbed mols. and extremely high CO2/N2 adsorption selectivities for CO2 adsorption from dry air and from gas mixts. typical of dry flue gas.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XitF2msb8%253D&md5=3d7fcc3d3e6b5aa43811c380337c0f07
82
Lin, L.-C.; Berger, A. H.; Martin, R. L.; Kim, J.; Swisher, J. a.; Jariwala, K.; Rycroft, C. H.; Bhown, A. S.; Deem, M. W.; Haranczyk, M.; Smit, B. In silico screening of carbon-capture materials. Nat. Mater. 2012, 11, 633– 641, DOI: 10.1038/nmat3336
[Crossref], [PubMed], [CAS], Google Scholar
82
In silico screening of carbon-capture materials
Lin, Li-Chiang; Berger, Adam H.; Martin, Richard L.; Kim, Jihan; Swisher, Joseph A.; Jariwala, Kuldeep; Rycroft, Chris H.; Bhown, Abhoyjit S.; Deem, Michael W.; Haranczyk, Maciej; Smit, Berend
Nature Materials (2012), 11 (7), 633-641CODEN: NMAACR; ISSN:1476-1122. (Nature Publishing Group)
One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to sep. the CO2 from flue gas. For example, near-term CCS technol. applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. The authors developed a computational approach to rank adsorbents for their performance in CCS. Using this anal., hundreds of thousands of zeolite and zeolitic imidazolate framework structures were screened and many different structures identified that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XnsFKgs7o%253D&md5=492bbeb4268dbad4726e14b2df4a38bf
83
Qiao, Z.; Zhang, K.; Jiang, J. In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation. J. Mater. Chem. A 2016, 4, 2105– 2114, DOI: 10.1039/C5TA08984K
[Crossref], [CAS], Google Scholar
83
In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation
Qiao, Zhiwei; Zhang, Kang; Jiang, Jianwen
Journal of Materials Chemistry A: Materials for Energy and Sustainability (2016), 4 (6), 2105-2114CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
We report a mol. simulation study to screen 4764 computation-ready, exptl. metal-org. frameworks (CoRE-MOFs) for CO2 sepn. from flue gas (CO2/N2) and natural gas (CO2/CH4). Quant. relationships are established, for the first time, between the metal type and adsorbent evaluation criteria (adsorption selectivity and capacity, working capacity and regenerability). It is found that alkalis exist in 75% of alkali-MOFs as nonframework ions or open metal sites, and 75% of alk.-MOFs contain alkalines as open metal sites; thus alkali- and alk.-MOFs exhibit high adsorption selectivity and large capacity. Combining selectivity, working capacity and regenerability, however, alkali- and alk.-MOFs possess the lowest performance for CO2 sepn. Among ∼1000 lanthanide-based CoRE-MOFs, 50% contain lanthanides as open metal sites and have the highest performance. The best 30 CoRE-MOFs are identified for CO2/N2 and CO2/CH4 sepn., and they mostly contain lanthanides. Furthermore, we predict the breakthrough curves in two identified CoRE-MOFs and demonstrate their superior sepn. performance. This modeling study highlights the central importance of adsorbent evaluation by holistic criteria, and suggests that lanthanides could be interesting metals in the design of new MOFs for CO2 sepn.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVCltbjI&md5=729fc33df7b0e0d675eb68f03a7b9797
84
Wilmer, C. E.; Leaf, M.; Lee, C. Y.; Farha, O. K.; Hauser, B. G.; Hupp, J. T.; Snurr, R. Q. Large-scale screening of hypothetical metal-organic frameworks. Nat. Chem. 2012, 4, 83– 89, DOI: 10.1038/nchem.1192
[Crossref], [CAS], Google Scholar
84
Large-scale screening of hypothetical metal-organic frameworks
Wilmer, Christopher E.; Leaf, Michael; Lee, Chang Yeon; Farha, Omar K.; Hauser, Brad G.; Hupp, Joseph T.; Snurr, Randall Q.
Nature Chemistry (2012), 4 (2), 83-89CODEN: NCAHBB; ISSN:1755-4330. (Nature Publishing Group)
Metal-org. frameworks (MOFs) are porous materials constructed from modular mol. building blocks, typically metal clusters and org. linkers. These can, in principle, be assembled to form an almost unlimited no. of MOFs, yet materials reported to date represent only a tiny fraction of the possible combinations. Here, the authors demonstrate a computational approach to generate all conceivable MOFs from a given chem. library of building blocks (based on the structures of known MOFs) and rapidly screen them to find the best candidates for a specific application. From a library of 102 building blocks the authors generated 137,953 hypothetical MOFs and for each calcd. the pore-size distribution, surface area and methane-storage capacity. The authors identified over 300 MOFs with a predicted methane-storage capacity better than that of any known material, and this approach also revealed structure-property relations. Methyl-functionalized MOFs were frequently top performers, so the authors selected one such promising MOF and exptl. confirmed its predicted capacity.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVagtL3K&md5=3becbfed2fdacdb8b58146666da7c038
85
Simon, C. M.; Kim, J.; Gomez-Gualdron, D. a.; Camp, J. S.; Chung, Y. G.; Martin, R. L.; Mercado, R.; Deem, M. W.; Gunter, D.; Haranczyk, M.; Sholl, D. S.; Snurr, R. Q.; Smit, B. The materials genome in action: identifying the performance limits for methane storage. Energy Environ. Sci. 2015, 8, 1190– 1199, DOI: 10.1039/C4EE03515A
[Crossref], [CAS], Google Scholar
85
The materials genome in action: identifying the performance limits for methane storage
Simon, Cory M.; Kim, Jihan; Gomez-Gualdron, Diego A.; Camp, Jeffrey S.; Chung, Yongchul G.; Martin, Richard L.; Mercado, Rocio; Deem, Michael W.; Gunter, Dan; Haranczyk, Maciej; Sholl, David S.; Snurr, Randall Q.; Smit, Berend
Energy & Environmental Science (2015), 8 (4), 1190-1199CODEN: EESNBY; ISSN:1754-5706. (Royal Society of Chemistry)
Analogous to the way the Human Genome Project advanced an array of biol. sciences by mapping the human genome, the Materials Genome Initiative aims to enhance our understanding of the fundamentals of materials science by providing the information we need to accelerate the development of new materials. This approach is particularly applicable to recently developed classes of nanoporous materials, such as metal-org. frameworks (MOFs), which are synthesized from a limited set of mol. building blocks that can be combined to generate a very large no. of different structures. In this Perspective, we illustrate how a materials genome approach can be used to search for high-performance adsorbent materials to store natural gas in a vehicular fuel tank. Drawing upon recent reports of large databases of existing and predicted nanoporous materials generated in silico, we have collected and compared on a consistent basis the methane uptake in over 650 000 materials based on the results of mol. simulation. The data that we have collected provide candidate structures for synthesis, reveal relationships between structural characteristics and performance, and suggest that it may be difficult to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXotVOguw%253D%253D&md5=cb589b6b987ef80816a74c377774980c
86
Huck, J. M.; Lin, L.-C.; Berger, A. H.; Shahrak, M. N.; Martin, R. L.; Bhown, A. S.; Haranczyk, M.; Reuter, K.; Smit, B. Evaluating different classes of porous materials for carbon capture. Energy Environ. Sci. 2014, 7, 4132– 4146, DOI: 10.1039/C4EE02636E
[Crossref], [CAS], Google Scholar
86
Evaluating different classes of porous materials for carbon capture
Huck, Johanna M.; Lin, Li-Chiang; Berger, Adam H.; Shahrak, Mahdi Niknam; Martin, Richard L.; Bhown, Abhoyjit S.; Haranczyk, Maciej; Reuter, Karsten; Smit, Berend
Energy & Environmental Science (2014), 7 (12), 4132-4146CODEN: EESNBY; ISSN:1754-5706. (Royal Society of Chemistry)
Carbon Capture and Sequestration (CCS) is one of the promising ways to significantly reduce the CO2 emission from power plants. In particular, amongst several sepn. strategies, adsorption by nano-porous materials is regarded as a potential means to efficiently capture CO2 at the place of its origin in a post-combustion process. The search for promising materials in such a process not only requires the screening of a multitude of materials but also the development of an adequate evaluation metric. Several evaluation criteria have been introduced in the literature concg. on a single adsorption or material property at a time. Parasitic energy is a new approach for material evaluation to address the energy load imposed on a power plant while applying CCS. In this work, we evaluate over 60 different materials with respect to their parasitic energy, including exptl. realized and hypothetical materials such as metal-org. frameworks (MOFs), zeolitic imidazolate frameworks (ZIFs), porous polymer networks (PPNs), and zeolites. The results are compared to other proposed evaluation criteria and performance differences are studied regarding the regeneration modes, (i.e.Pressure-Swing (PSA) and Temp.-Swing Adsorption (TSA)) as well as the flue gas compn.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhslGgurbO&md5=f191b21536f25b460c1867f13076745b
87
Burns, T. D.; Pai, K. N.; Subraveti, S. G.; Collins, S. P.; Krykunov, M.; Rajendran, A.; Woo, T. K. Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Postcombustion CO 2 Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models. Environ. Sci. Technol. 2020, 54, 4536, DOI: 10.1021/acs.est.9b07407
[ACS Full Text ], [CAS], Google Scholar
87
Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Post-combustion CO2 Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models
Burns, Thomas D.; Pai, Kasturi Nagesh; Subraveti, Sai Gokul; Collins, Sean P.; Krykunov, Mykhaylo; Rajendran, Arvind; Woo, Tom K.
Environmental Science & Technology (2020), 54 (7), 4536-4544CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
Post-combustion CO2 capture and storage (CCS) is a key technol. approach to reduce greenhouse gas emissions while humans transition to C-free energy prodn.; however, current solvent-based CO2 capture processes are considered too energetically expensive for widespread deployment. Vacuum swing adsorption (VSA) is a low-energy CCS with the potential for industrial implementation if the right sorbents can be found. Metal-org. framework (MOF) materials are often promoted as sorbents for low-energy CCS by highlighting select adsorption properties without a clear understanding of how they perform in actual VSA processes. Atomistic simulations were fully integrated with a detailed VSA simulator and validated on a pilot scale to screen 1632 exptl. characterized MOF. A total of 482 materials were obsd. to meet the 95% CO2 purity and 90% CO2 recovery targets (95/90-PRT), 365 of which have parasitic energies below that of solvent-based capture (∼290 kWhe/MT CO2) with a low value of 217 kWhe/MT CO2. Machine learning models were developed using common adsorption metrics to predict a material ability to meet the 95/90-PRT with an overall 91% prediction accuracy. Accurate parasitic energy and productivity ests. of a VSA process require full process simulations.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXjs1Wisbo%253D&md5=7fa2c34868cac38202973c1cb71d6793
88
Farmahini, A. H.; Krishnamurthy, S.; Friedrich, D.; Brandani, S.; Sarkisov, L. From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes. Ind. Eng. Chem. Res. 2018, 57, 15491– 15511, DOI: 10.1021/acs.iecr.8b03065
[ACS Full Text ], [CAS], Google Scholar
88
From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes
Farmahini, Amir H.; Krishnamurthy, Shreenath; Friedrich, Daniel; Brandani, Stefano; Sarkisov, Lev
Industrial & Engineering Chemistry Research (2018), 57 (45), 15491-15511CODEN: IECRED; ISSN:0888-5885. (American Chemical Society)
Multiscale material screening strategies combine mol. simulations and process modeling to identify the best performing adsorbents for a particular application, such as carbon capture. The idea to go from the properties of a single crystal to the prediction of material performance in a real process is both powerful and appealing; however, it is yet to be established how to implement it consistently. In this article, we focus on the challenges assocd. with the interface between mol. and process levels of description. We explore how predictions of the material performance in the actual process depend on the accuracy of mol. simulations, on the procedures to feed the equil. adsorption data into the process simulator, and on the structural characteristics of the pellets, which are not available from mol. simulations and should be treated as optimization parameters. The presented anal. paves the way for more consistent and robust multiscale material screening strategies.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhvVKltL3J&md5=d9f237b44447928b5db6d4eea3df209f
89
Farmahini, H.; Friedrich, A.; Brandani, D.; Sarkisov, S.; Exploring, L. new sources of efficiency in process-driven materials screening for post-combustion carbon capture. Energy Environ. Sci. 2020, 13, 1018– 1037, DOI: 10.1039/C9EE03977E
[Crossref], Google Scholar
There is no corresponding record for this reference.
90
AiiDA-LSMO plugin. github.com/lsmo-epfl/aiida-lsmo (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
91
Open Science Means Open Source—Or, at Least, It Should. linuxjournal.com/content/open-science-means-open-source-or-least-it-should (accessed on July 2020).
Google Scholar
There is no corresponding record for this reference.
92
Codes—NOMAD CoE. www.nomad-coe.eu/index.php?page=codes (accessed on July 2020).
Google Scholar
There is no corresponding record for this reference.
93
Ghiringhelli, L. M.; Carbogno, C.; Levchenko, S.; Mohamed, F.; Huhs, G.; Lüders, M.; Oliveira, M.; Scheffler, M. Towards efficient data exchange and sharing for big-data driven materials science: Metadata and data formats. npj Comput. Mater. 2017, 3, 1– 9, DOI: 10.1038/s41524-017-0048-5
[Crossref], [CAS], Google Scholar
93
Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats
Ghiringhelli, Luca M.; Carbogno, Christian; Levchenko, Sergey; Mohamed, Fawzi; Huhs, Georg; Lueders, Martin; Oliveira, Micael; Scheffler, Matthias
npj Computational Materials (2017), 3 (1), 1-9CODEN: NCMPCS; ISSN:2057-3960. (Nature Research)
With big-data driven materials research, the new paradigm of materials science, sharing and wide accessibility of data are becoming crucial aspects. Obviously, a prerequisite for data exchange and big-data analytics is standardization, which means using consistent and unique conventions for, e.g., units, zero base lines, and file formats. There are two main strategies to achieve this goal. One accepts the heterogeneous nature of the community, which comprises scientists from physics, chem., bio-physics, and materials science, by complying with the diverse ecosystem of computer codes and thus develops "converters" for the input and output files of all important codes. These converters then translate the data of each code into a standardized, code-independent format. The other strategy is to provide standardized open libraries that code developers can adopt for shaping their inputs, outputs, and restart files, directly into the same code-independent format. In this perspective paper, we present both strategies and argue that they can and should be regarded as complementary, if not even synergetic. The represented appropriate format and conventions were agreed upon by two teams, the Electronic Structure Library (ESL) of the European Center for Atomic and Mol. Computations (CECAM) and the NOvel MAterials Discovery (NOMAD) Lab., a European Center of Excellence (CoE). A key element of this work is the definition of hierarchical metadata describing state-of-the-art electronic-structure calcns.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1CjsL7L&md5=d24d2dbaf0f5bf0780228166cc56cd14
94
Clark, S. J.; Segall, M. D.; Pickard, C. J.; Hasnip, P. J.; Probert, M. I. J.; Refson, K.; Payne, M. C. First principles methods using CASTEP. Z. Kristallogr. - Cryst. Mater. 2005, 220, 567– 570, DOI: 10.1524/zkri.220.5.567.65075
[Crossref], [CAS], Google Scholar
94
First principles methods using CASTEP
Clark, Stewart J.; Segall, Matthew D.; Pickard, Chris J.; Hasnip, Phil J.; Probert, Matt I. J.; Refson, Keith; Payne, Mike C.
Zeitschrift fuer Kristallographie (2005), 220 (5-6), 567-570CODEN: ZEKRDZ; ISSN:0044-2968. (Oldenbourg Wissenschaftsverlag GmbH)
The CASTEP code for first principles electronic structure calcns. is described. A brief, non-tech. overview is given and some of the features and capabilities highlighted. Some features which are unique to CASTEP are described and near-future development plans outlined.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXmsVSitbk%253D&md5=edb75e2f9d4df4ad83f4df7db21888e7
95
CASTEP website. www.castep.org/CASTEP/GettingCASTEP (accessed on June 2020).
Google Scholar
There is no corresponding record for this reference.
96
Fdez. Galván, I. OpenMolcas: From Source Code to Insight. J. Chem. Theory Comput. 2019, 15, 5925– 5964, DOI: 10.1021/acs.jctc.9b00532
[ACS Full Text ], [CAS], Google Scholar
96
OpenMolcas: From Source Code to Insight
Fdez. Galvan, Ignacio; Vacher, Morgane; Alavi, Ali; Angeli, Celestino; Aquilante, Francesco; Autschbach, Jochen; Bao, Jie J.; Bokarev, Sergey I.; Bogdanov, Nikolay A.; Carlson, Rebecca K.; Chibotaru, Liviu F.; Creutzberg, Joel; Dattani, Nike; Delcey, Mickael G.; Dong, Sijia S.; Dreuw, Andreas; Freitag, Leon; Frutos, Luis Manuel; Gagliardi, Laura; Gendron, Frederic; Giussani, Angelo; Gonzalez, Leticia; Grell, Gilbert; Guo, Meiyuan; Hoyer, Chad E.; Johansson, Marcus; Keller, Sebastian; Knecht, Stefan; Kovacevic, Goran; Kaellman, Erik; Li Manni, Giovanni; Lundberg, Marcus; Ma, Yingjin; Mai, Sebastian; Malhado, Joao Pedro; Malmqvist, Per Aake; Marquetand, Philipp; Mewes, Stefanie A.; Norell, Jesper; Olivucci, Massimo; Oppel, Markus; Phung, Quan Manh; Pierloot, Kristine; Plasser, Felix; Reiher, Markus; Sand, Andrew M.; Schapiro, Igor; Sharma, Prachi; Stein, Christopher J.; Soerensen, Lasse Kragh; Truhlar, Donald G.; Ugandi, Mihkel; Ungur, Liviu; Valentini, Alessio; Vancoillie, Steven; Veryazov, Valera; Weser, Oskar; Wesolowski, Tomasz A.; Widmark, Per-Olof; Wouters, Sebastian; Zech, Alexander; Zobel, J. Patrick; Lindh, Roland
Journal of Chemical Theory and Computation (2019), 15 (11), 5925-5964CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
In this Article we describe the OpenMolcas environment and invite the computational chem. community to collaborate. The open-source project already includes a large no. of new developments realized during the transition from the com. MOLCAS product to the open-source platform. The paper initially describes the tech. details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space SCF, d. matrix renormalization group (DMRG) methods, and hybrid multiconfigurational wave function and d. functional theory models. Some of these implementations include an array of addnl. options and functionalities. The paper proceeds and describes developments related to explorations of potential energy surfaces. Here we present methods for the optimization of conical intersections, the simulation of adiabatic and nonadiabatic mol. dynamics, and interfaces to tools for semiclassical and quantum mech. nuclear dynamics. Furthermore, the Article describes features unique to simulations of spectroscopic and magnetic phenomena such as the exact semiclassical description of the interaction between light and matter, various X-ray processes, magnetic CD, and properties. Finally, the paper describes a no. of built-in and add-on features to support the OpenMolcas platform with postcalcn. anal. and visualization, a multiscale simulation option using frozen-d. embedding theory, and new electronic and muonic basis sets.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhslKisbzM&md5=8b7ad4e027cd26706579b8717897e8b4
97
Butler, K. T.; Davies, D. W.; Cartwright, H.; Isayev, O.; Walsh, A. Machine learning for molecular and materials science. Nature 2018, 559, 547– 555, DOI: 10.1038/s41586-018-0337-2
[Crossref], [PubMed], [CAS], Google Scholar
97
Machine learning for molecular and materials science
Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh; Isayev, Olexandr; Walsh, Aron
Nature (London, United Kingdom) (2018), 559 (7715), 547-555CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
Here we summarize recent progress in machine learning for the chem. sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of mols. and materials is accelerated by artificial intelligence.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtl2jt7vL&md5=13d36f27db8d59f558fe28e946b4b009
98
Anderson, R.; Biong, A.; Gómez-Gualdrón, D. A. Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model. J. Chem. Theory Comput. 2020, 16, 1271– 1283, DOI: 10.1021/acs.jctc.9b00940
[ACS Full Text ], [CAS], Google Scholar
98
Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model
Anderson, Ryther; Biong, Achay; Gomez-Gualdron, Diego A.
Journal of Chemical Theory and Computation (2020), 16 (2), 1271-1283CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
Tailoring the structure and chem. of metal-org. frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), mol. simulation has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent expts. to focus only on a small subset of the most promising MOFs. In many instances, however, even mol. simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede mol. simulation efforts. In this study, as a proof of concept, we trained a neural network - specifically, a multilayer perceptron (MLP) - as the first example of a machine learning model capable of predicting full adsorption isotherms of different mols. not included in the training of the model. To achieve this, we trained our MLP on "alchem." species, represented only by variables derived from their force field parameters, to predict the loadings of real adsorbates. MOFs were also represented by simple descriptors (e.g. geometric properties and chem. moieties). Alchem. species used for training were small, near-spherical, and nonpolar, enabling the prediction of analogous real mols. relevant for chem. sepns. such as argon, krypton, xenon, methane, ethane, and nitrogen. The trained model was shown to make accurate adsorption predictions for these six adsorbates in both hypothetical and existing MOFs. The MLP presented here is not expected to be applied "as is" to more complex adsorbates with properties not considered during its training. However, our results illustrate a new philosophy of training that can be built upon with the goal of predicting adsorption isotherms in not only a database of MOFs, but also for a database of adsorbates, and over a range of relevant operating conditions.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXnsl2gtA%253D%253D&md5=1294e3fa83333f3f2e91f212d8d12502
99
Borboudakis, G.; Stergiannakos, T.; Frysali, M.; Klontzas, E.; Tsamardinos, I.; Froudakis, G. E. Chemically intuited, large-scale screening of MOFs by machine learning techniques. npj Comput. Mater. 2017, 3, 40, DOI: 10.1038/s41524-017-0045-8
[Crossref], Google Scholar
There is no corresponding record for this reference.
100
Fanourgakis, G. S.; Gkagkas, K.; Tylianakis, E.; Klontzas, E.; Froudakis, G. A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials. J. Phys. Chem. A 2019, 123, 6080– 6087, DOI: 10.1021/acs.jpca.9b03290
[ACS Full Text ], [CAS], Google Scholar
100
A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials
Fanourgakis, George S.; Gkagkas, Konstantinos; Tylianakis, Emmanuel; Klontzas, Emmanuel; Froudakis, George
Journal of Physical Chemistry A (2019), 123 (28), 6080-6087CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
In the present study, we propose a new set of descriptors that, along with a few structural features of nanoporous materials, can be used by machine learning algorithms for accurate predictions of the gas uptake capacities of these materials. All new descriptors closely resemble the helium atom void fraction of the material framework. However, instead of a helium atom, a particle with an appropriately defined van der Waals radius is used. The set of void fractions of a small no. of these particles is found to be sufficient to characterize uniquely the structure of each material and to account for the most important topol. features. We assess the accuracy of our approach by examg. the predictions of the random forest algorithm in the relative small dataset of the computation-ready, exptl. (CoRE) MOFs (∼4700 structures) that have been exptl. synthesized and whose geometrical/structural features have been accurately calcd. before. We first performed grand canonical Monte Carlo simulations to accurately det. their methane uptake capacities at two different temps. (280 and 298 K) and three different pressures (1, 5.8, and 65 bar). Despite the high chem. and structural diversity of the CoRE MOFs, it was found that the use of the proposed descriptors significantly improves the accuracy of the machine learning algorithm, particularly at low pressures, compared to the predictions made based solely on the rest structural features. More importantly, the algorithm can be easily adapted for other types of nanoporous materials beyond MOFs. Convergence of the predictions was reached even for small training set sizes compared to what was found in previous works using the hypothetical MOF database.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhtFaqs7zL&md5=bc12ae914f0e452aa0d178a6f65ce673
101
Korolev, V.; Mitrofanov, A.; Korotcov, A.; Tkachenko, V. Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability. J. Chem. Inf. Model. 2020, 60, 22– 28, DOI: 10.1021/acs.jcim.9b00587
[ACS Full Text ], [CAS], Google Scholar
101
Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability
Korolev, Vadim; Mitrofanov, Artem; Korotcov, Alexandru; Tkachenko, Valery
Journal of Chemical Information and Modeling (2020), 60 (1), 22-28CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
Nowadays the development of new functional materials/chem. compds. using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chem. structure representation. The classical approach of rigorous feature engineering in ML typically improves the performance of the predictive model, but at the same time, it narrows down the scope of applicability and decreases the phys. interpretability of predicted results. In this study, we present graph convolutional neural networks (GCNNs) as an architecture that allows for successfully predicting the properties of compds. from diverse domains of chem. space, using a minimal set of meaningful descriptors. The applicability of GCNN models has been demonstrated by a wide range of chem. domain-specific properties. Their performance is comparable to state-of-the-art techniques; however, this architecture exempts from the need to carry out precise feature engineering.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXisVGhtb3K&md5=04c9ffece81627cb0c2bdf8d2afccfda
102
Kapelewski, M. T.; Runčevski, T.; Tarver, J. D.; Jiang, H. Z.; Hurst, K. E.; Parilla, P. A.; Ayala, A.; Gennett, T.; Fitzgerald, S. A.; Brown, C. M.; Long, J. R. Record High Hydrogen Storage Capacity in the Metal-Organic Framework Ni 2 (m-dobdc) at Near-Ambient Temperatures. Chem. Mater. 2018, 30, 8179– 8189, DOI: 10.1021/acs.chemmater.8b03276
[ACS Full Text ], [CAS], Google Scholar
102
Record High Hydrogen Storage Capacity in the Metal-Organic Framework Ni2(m-dobdc) at Near-Ambient Temperatures
Kapelewski, Matthew T.; Runcevski, Tomce; Tarver, Jacob D.; Jiang, Henry Z. H.; Hurst, Katherine E.; Parilla, Philip A.; Ayala, Anthony; Gennett, Thomas; FitzGerald, Stephen A.; Brown, Craig M.; Long, Jeffrey R.
Chemistry of Materials (2018), 30 (22), 8179-8189CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
H holds promise as a clean alternative automobile fuel, but its on-board storage presents significant challenges due to the low temps. and/or high pressures required to achieve a sufficient energy d. The opportunity to significantly reduce the required pressure for high d. H2 storage persists for metal-org. frameworks due to their modular structures and large internal surface areas. The measurement of H2 adsorption in such materials under conditions most relevant to on-board storage is crucial to understanding how these materials would perform in actual applications, although such data have to date been lacking. In the present work, the metal-org. frameworks M2(m-dobdc) (M = Co, Ni; m-dobdc4- =4,6-dioxido-1,3-benzenedicarboxylate) and the isomeric frameworks M2(dobdc) (M = Co, Ni; dobdc4- =1,4-dioxido-1,3-benzenedicarboxylate), which are known to have open metal cation sites that strongly interact with H, were evaluated for their usable volumetric H2 storage capacities over a range of near-ambient temps. relevant to on-board storage. Based upon adsorption isotherm data, Ni2(m-dobdc) was found to be the top-performing physisorptive storage material with a usable volumetric capacity between 100 and 5 bar of 11.0 g/L at 25° and 23.0 g/L with a temp. swing between -75 and 25°. Addnl. neutron diffraction and IR spectroscopy expts. performed with in situ dosing of D2 or H2 were used to probe the hydrogen storage properties of these materials under the relevant conditions. The results provide benchmark characteristics for comparison with future attempts to achieve improved adsorbents for mobile hydrogen storage applications. Flammable H gas is used at high pressures and low temps. in this study. This is dangerous both from a flammability perspective and from the perspective of working with gases at high pressures, both of which can create situations that are dangerous if the proper procedures are not followed.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXitFSgs7bK&md5=e2849e4f29e9c0520e14e9bd867b50f1
103
We calculated an average of ca. 1000 core hours, with parallel calculations, for the evaluation of a COF for the seven applications reported as proof of concept. Of these, about two-thirds are dedicated to the cell optimization via DFT. The pricing for the coffee analogy has been estimated from the cost of commercial pay-per-use computation time.
There is no corresponding record for this reference.
104
Talirz, L. Materials Cloud, a platform for open computational science. Sci. Data 2020, 7, 299, DOI: 10.1038/s41597-020-00637-5
[Crossref], [PubMed], [CAS], Google Scholar
104
Materials Cloud, a platform for open computational science
Talirz Leopold; Kumbhar Snehal; Passaro Elsa; Yakutovich Aliaksandr V; Granata Valeria; Gargiulo Fernando; Borelli Marco; Uhrin Martin; Huber Sebastiaan P; Zoupanos Spyros; Adorf Carl S; Andersen Casper Welzel; Schutt Ole; Pignedoli Carlo A; Passerone Daniele; VandeVondele Joost; Schulthess Thomas C; Smit Berend; Pizzi Giovanni; Marzari Nicola; Talirz Leopold; Kumbhar Snehal; Passaro Elsa; Yakutovich Aliaksandr V; Granata Valeria; Gargiulo Fernando; Borelli Marco; Uhrin Martin; Huber Sebastiaan P; Zoupanos Spyros; Adorf Carl S; Andersen Casper Welzel; Pizzi Giovanni; Marzari Nicola; Talirz Leopold; Passaro Elsa; Yakutovich Aliaksandr V; Smit Berend; VandeVondele Joost; Schulthess Thomas C; VandeVondele Joost; Schulthess Thomas C
Scientific data (2020), 7 (1), 299 ISSN:.
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their provenance graph, (2) modelling services and virtual machines, (3) tools for data analytics, and pre-/post-processing, and (4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow retracing and reproducing any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38blvFyksQ%253D%253D&md5=cc3308e970dbb0e3e6719dfb0efb1e9f
105
Kühne, T. D. CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations. J. Chem. Phys. 2020, 152, 194103, DOI: 10.1063/5.0007045
[Crossref], [PubMed], [CAS], Google Scholar
105
CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations
Kuehne, Thomas D.; Iannuzzi, Marcella; Del Ben, Mauro; Rybkin, Vladimir V.; Seewald, Patrick; Stein, Frederick; Laino, Teodoro; Khaliullin, Rustam Z.; Schuett, Ole; Schiffmann, Florian; Golze, Dorothea; Wilhelm, Jan; Chulkov, Sergey; Bani-Hashemian, Mohammad Hossein; Weber, Valery; Borstnik, Urban; Taillefumier, Mathieu; Jakobovits, Alice Shoshana; Lazzaro, Alfio; Pabst, Hans; Mueller, Tiziano; Schade, Robert; Guidon, Manuel; Andermatt, Samuel; Holmberg, Nico; Schenter, Gregory K.; Hehn, Anna; Bussy, Augustin; Belleflamme, Fabian; Tabacchi, Gloria; Gloess, Andreas; Lass, Michael; Bethune, Iain; Mundy, Christopher J.; Plessl, Christian; Watkins, Matt; VandeVondele, Joost; Krack, Matthias; Hutter, Juerg
Journal of Chemical Physics (2020), 152 (19), 194103CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)
A review. CP2K is an open source electronic structure and mol. dynamics software package to perform atomistic simulations of solid-state, liq., mol., and biol. systems. It is esp. aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio mol. dynamics simulations. Excellent performance for electronic structure calcns. is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on d. functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension. (c) 2020 American Institute of Physics.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtVSgtrzF&md5=b9e5975bc402f0d53e2d99da998adf5f
106
Dubbeldam, D.; Calero, S.; Ellis, D. E.; Snurr, R. Q. RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials. Mol. Simul. 2016, 42, 81– 101, DOI: 10.1080/08927022.2015.1010082
[Crossref], [CAS], Google Scholar
106
RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials
Dubbeldam, David; Calero, Sofia; Ellis, Donald E.; Snurr, Randall Q.
Molecular Simulation (2016), 42 (2), 81-101CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)
A new software package, RASPA, for simulating adsorption and diffusion of mols. in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for mol. dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXjsFGnur8%253D&md5=5dc7918d850fc8cfbc84de07f59f415c
107
Manz, T. A.; Limas, N. G. Introducing DDEC6 atomic population analysis: part 1. charge partitioning theory and methodology. RSC Adv. 2016, 6, 47771– 47801, DOI: 10.1039/C6RA04656H
[Crossref], [CAS], Google Scholar
107
Introducing DDEC6 atomic population analysis: part 1. Charge partitioning theory and methodology
Manz, Thomas A.; Limas, Nidia Gabaldon
RSC Advances (2016), 6 (53), 47771-47801CODEN: RSCACL; ISSN:2046-2069. (Royal Society of Chemistry)
Net at. charges (NACs) are widely used in all chem. sciences to concisely summarize key information about the partitioning of electrons among atoms in materials. The objective of this article is to develop an at. population anal. method that is suitable to be used as a default method in quantum chem. programs irresp. of the kind of basis sets employed. To address this challenge, we introduce a new atoms-in-materials method with the following nine properties: (1) exactly one electron distribution is assigned to each atom, (2) core electrons are assigned to the correct host atom, (3) NACs are formally independent of the basis set type because they are functionals of the total electron distribution, (4) the assigned at. electron distributions give an efficiently converging polyat. multipole expansion, (5) the assigned NACs usually follow Pauling scale electronegativity trends, (6) NACs for a particular element have good transferability among different conformations that are equivalently bonded, (7) the assigned NACs are chem. consistent with the assigned at. spin moments, (8) the method has predictably rapid and robust convergence to a unique soln., and (9) the computational cost of charge partitioning scales linearly with increasing system size. We study numerous materials as examples: (a) a series of endohedral C60 complexes, (b) high-pressure compressed sodium chloride crystals with unusual stoichiometries, (c) metal-org. frameworks, (d) large and small mols., (e) organometallic complexes, (f) various solids, and (g) solid surfaces. Due to non-nuclear attractors, Bader's quantum chem. topol. could not assign NACs for some of these materials. We show for the first time that the Iterative Hirshfeld and DDEC3 methods do not always converge to a unique soln. independent of the initial guess, and this sometimes causes those methods to assign dramatically different NACs on symmetry-equiv. atoms. By using a fixed no. of charge partitioning steps with well-defined ref. ion charges, the DDEC6 method avoids this problem by always converging to a unique soln. These characteristics make the DDEC6 method ideally suited for use as a default charge assignment method in quantum chem. programs.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XmslKmsbw%253D&md5=c456d3f0bfcba3e16fad5a492702627e
108
Wang, Y.; Liu, H.; Pan, Q.; Wu, C.; Hao, W.; Xu, J.; Chen, R.; Liu, J.; Li, Z.; Zhao, Y. Construction of Fully Conjugated Covalent Organic Frameworks via Facile Linkage Conversion for Efficient Photoenzymatic Catalysis. J. Am. Chem. Soc. 2020, 142, 5958– 5963, DOI: 10.1021/jacs.0c00923
[ACS Full Text ], [CAS], Google Scholar
108
Construction of fully conjugated covalent organic frameworks via facile linkage conversion for efficient photoenzymatic catalysis
Wang, Yuancheng; Liu, Hui; Pan, Qingyan; Wu, Chenyu; Hao, Wenbo; Xu, Jie; Chen, Renzeng; Liu, Jian; Li, Zhibo; Zhao, Yingjie
Journal of the American Chemical Society (2020), 142 (13), 5958-5963CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
Covalent org. frameworks (COFs) with improved stability and extended π-conjugation structure are highly desirable. Here, two imine-linked COFs were converted into ultrastable and π-conjugated fused-arom. thieno[3,2-c]pyridine-linked COFs (B-COF-2 and T-COF-2). The successful conversion was confirmed by IR and solid-state 13C NMR spectroscopies. Furthermore, the structures of thieno[3,2-c]pyridine-linked COFs were evaluated by TEM and PXRD. It is noted that a slight difference in the structure leads to totally different photoactivity. The fully π-conjugated T-COF-2 contg. triazine as the core exhibited an excellent photocatalytic NADH regeneration yield of 74% in 10 min.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXkvFWgu7Y%253D&md5=466297c12380bae004511b0b918ef548
109
Yan, S.; Guan, X.; Li, H.; Li, D.; Xue, M.; Yan, Y.; Valtchev, V.; Qiu, S.; Fang, Q. Three-dimensional Salphen-based Covalent-Organic Frameworks as Catalytic Antioxidants. J. Am. Chem. Soc. 2019, 141, 2920– 2924, DOI: 10.1021/jacs.9b00485
[ACS Full Text ], [CAS], Google Scholar
109
Three-dimensional Salphen-based Covalent-Organic Frameworks as Catalytic Antioxidants
Yan, Shichen; Guan, Xinyu; Li, Hui; Li, Daohao; Xue, Ming; Yan, Yushan; Valtchev, Valentin; Qiu, Shilun; Fang, Qianrong
Journal of the American Chemical Society (2019), 141 (7), 2920-2924CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
The development of three-dimensional (3D) functionalized covalent-org. frameworks (COFs) is of crit. importance for expanding their potential applications. However, the introduction of functional groups in 3D COFs remains largely unexplored. Herein, we report the first example of 3D Salphen-based COFs (3D-Salphen-COFs) and their metal-contg. counterparts (3D-M-Salphen-COFs). These Salphen-based COFs exhibit high crystallinity and sp. surface area in addn. to excellent chem. stability. Furthermore, the Cu(II)-Salphen COF displays high activity in the removal of superoxide radicals. This study not only presents a new pathway to construct 3D functionalized COFs but also promotes their applications in biol. and medicine.
>> More from SciFinder ^®
https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXisVSqtbc%253D&md5=ec6465fd28b90619afc02a0fad45ee0f
110
Ongari, D.; Yakutovich, A. V.; Talirz, L.; Smit, B. Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks; Materials Cloud Archive 2020.107. DOI: 10.24435/materialscloud:kd-wj .
Google Scholar
There is no corresponding record for this reference.

Cited By

This article is cited by 52 publications.

Bahram Hosseini Monjezi, Salih Okur, René Limbach, Abhinav Chandresh, Kaushik Sen, Tawheed Hashem, Matthias Schwotzer, Lothar Wondraczek, Christof Wöll, Alexander Knebel. Fast Dynamic Synthesis of MIL-68(In) Thin Films in High Optical Quality for Optical Cavity Sensing. ACS Nano 2023, 17 (6) , 6121-6130. https://doi.org/10.1021/acsnano.3c01558
Bowen Zheng, Felipe Lopes Oliveira, Rodrigo Neumann Barros Ferreira, Mathias Steiner, Hendrik Hamann, Grace X. Gu, Binquan Luan. Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2’s Chemisorption and Diffusion in Mg-MOF-74. ACS Nano 2023, 17 (6) , 5579-5587. https://doi.org/10.1021/acsnano.2c11102
Alexander Volkov, Jiashan Mi, Kanika Lalit, Puranjan Chatterjee, Dapeng Jing, Scott L. Carnahan, Yunhua Chen, Simin Sun, Aaron J. Rossini, Wenyu Huang, Levi M. Stanley. General Strategy for Incorporation of Functional Group Handles into Covalent Organic Frameworks via the Ugi Reaction. Journal of the American Chemical Society 2023, 145 (11) , 6230-6239. https://doi.org/10.1021/jacs.2c12440
Kolleboyina Jayaramulu, Soumya Mukherjee, Dulce M. Morales, Deepak P. Dubal, Ashok Kumar Nanjundan, Andreas Schneemann, Justus Masa, Stepan Kment, Wolfgang Schuhmann, Michal Otyepka, Radek Zbořil, Roland A. Fischer. Graphene-Based Metal–Organic Framework Hybrids for Applications in Catalysis, Environmental, and Energy Technologies. Chemical Reviews 2022, 122 (24) , 17241-17338. https://doi.org/10.1021/acs.chemrev.2c00270
Daniel W. Siderius, Harold W. Hatch, Vincent K. Shen. Temperature Extrapolation of Henry’s Law Constants and the Isosteric Heat of Adsorption. The Journal of Physical Chemistry B 2022, 126 (40) , 7999-8009. https://doi.org/10.1021/acs.jpcb.2c04583
Daniele Ongari, Leopold Talirz, Kevin Maik Jablonka, Daniel W. Siderius, Berend Smit. Data-Driven Matching of Experimental Crystal Structures and Gas Adsorption Isotherms of Metal–Organic Frameworks. Journal of Chemical & Engineering Data 2022, 67 (7) , 1743-1756. https://doi.org/10.1021/acs.jced.1c00958
Anna-Sophia Hehn, Beliz Sertcan, Fabian Belleflamme, Sergey K. Chulkov, Matthew B. Watkins, Jürg Hutter. Excited-State Properties for Extended Systems: Efficient Hybrid Density Functional Methods. Journal of Chemical Theory and Computation 2022, 18 (7) , 4186-4202. https://doi.org/10.1021/acs.jctc.2c00144
George C. Lisensky, Omar M. Yaghi. Visualizing Pore Packing and Topology in MOFs. Journal of Chemical Education 2022, 99 (5) , 1998-2004. https://doi.org/10.1021/acs.jchemed.2c00120
Sauradeep Majumdar, Seyed Mohamad Moosavi, Kevin Maik Jablonka, Daniele Ongari, Berend Smit. Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening. ACS Applied Materials & Interfaces 2021, 13 (51) , 61004-61014. https://doi.org/10.1021/acsami.1c16220
Vadim V. Korolev, Yuriy M. Nevolin, Thomas A. Manz, Pavel V. Protsenko. Parametrization of Nonbonded Force Field Terms for Metal–Organic Frameworks Using Machine Learning Approach. Journal of Chemical Information and Modeling 2021, 61 (12) , 5774-5784. https://doi.org/10.1021/acs.jcim.1c01124
Arni Sturluson, Ali Raza, Grant D. McConachie, Daniel W. Siderius, Xiaoli Z. Fern, Cory M. Simon. Recommendation System to Predict Missing Adsorption Properties of Nanoporous Materials. Chemistry of Materials 2021, 33 (18) , 7203-7216. https://doi.org/10.1021/acs.chemmater.1c01201
Maryam Chafiq, Abdelkarim Chaouiki, Young Gun Ko. Recent Advances in Multifunctional Reticular Framework Nanoparticles: A Paradigm Shift in Materials Science Road to a Structured Future. Nano-Micro Letters 2023, 15 (1) https://doi.org/10.1007/s40820-023-01180-9
Min Ying Tsang, Anna Sinelshchikova, Orysia Zaremba, Flora Schöfbeck, Alejandra Durán Balsa, Michael R. Reithofer, Stefan Wuttke, Jia Min Chin. Multilength Scale Hierarchy in Metal‐Organic Frameworks: Synthesis, Characterization and the Impact on Applications. Advanced Functional Materials 2023, 30 https://doi.org/10.1002/adfm.202308376
Valeria B. López-Cervantes, Juan L. Obeso, Ana Yañez-Aulestia, Alejandro Islas-Jácome, Carolina Leyva, Eduardo González-Zamora, Elí Sánchez-González, Ilich A. Ibarra. MFM-300(Sc): a chemically stable Sc( iii )-based MOF material for multiple applications. Chemical Communications 2023, 59 (69) , 10343-10359. https://doi.org/10.1039/D3CC02987E
Beatriz Mourino, Kevin Maik Jablonka, Andres Ortega‐Guerrero, Berend Smit. In Search of Covalent Organic Framework Photocatalysts: A DFT‐Based Screening Approach. Advanced Functional Materials 2023, 33 (32) https://doi.org/10.1002/adfm.202301594
Gokhan Onder Aksu, Seda Keskin. Advancing CH 4 /H 2 separation with covalent organic frameworks by combining molecular simulations and machine learning. Journal of Materials Chemistry A 2023, 11 (27) , 14788-14799. https://doi.org/10.1039/D3TA02433D
Hao Liu, Yifan Yao, Paolo Samorì. Taming Multiscale Structural Complexity in Porous Skeletons: From Open Framework Materials to Micro/Nanoscaffold Architectures. Small Methods 2023, 52 https://doi.org/10.1002/smtd.202300468
Mahyar Panahi‐Sarmad, Shakiba Samsami, Ahmadreza Ghaffarkhah, Seyyed Alireza Hashemi, Shayan Ghasemi, Majed Amini, Stefan Wuttke, Orlando Rojas, Kam Chiu Tam, Feng Jiang, Mohammad Arjmand, Farhad Ahmadijokani, Milad Kamkar. MOF‐Based Electromagnetic Shields Multiscale Design: Nanoscale Chemistry, Microscale Assembly, and Macroscale Manufacturing. Advanced Functional Materials 2023, 11 https://doi.org/10.1002/adfm.202304473
Hakan Demir, Hilal Daglar, Hasan Can Gulbalkan, Gokhan Onder Aksu, Seda Keskin. Recent advances in computational modeling of MOFs: From molecular simulations to machine learning. Coordination Chemistry Reviews 2023, 484 , 215112. https://doi.org/10.1016/j.ccr.2023.215112
Jing Wang, Kai Tian, Dongyang Li, Muning Chen, Xiaoquan Feng, Yatao Zhang, Yong Wang, Bart Van der Bruggen. Machine learning in gas separation membrane developing: Ready for prime time. Separation and Purification Technology 2023, 313 , 123493. https://doi.org/10.1016/j.seppur.2023.123493
H. Martínez-Pérez-Cejuela, Raquel B. R. Mesquita, E. F. Simó-Alfonso, J. M. Herrero-Martínez, António O. S. S. Rangel. Combining microfluidic paper-based platform and metal–organic frameworks in a single device for phenolic content assessment in fruits. Microchimica Acta 2023, 190 (4) https://doi.org/10.1007/s00604-023-05702-5
Salvador R. G. Balestra, Bruno Martínez-Haya, Norge Cruz-Hernández, Dewi W. Lewis, Scott M. Woodley, Rocio Semino, Guillaume Maurin, A. Rabdel Ruiz-Salvador, Said Hamad. Nucleation of zeolitic imidazolate frameworks: from molecules to nanoparticles. Nanoscale 2023, 15 (7) , 3504-3519. https://doi.org/10.1039/D2NR06521E
Zhaoyu Han, Yue Qian, Xiyue Gao, Dutao Yang, Yanfei Cai, Yun Chen, Jian Jin, Zhaoqi Yang. Hypoxia-responsive covalent organic framework by single NIR laser-triggered for multimodal synergistic therapy of triple-negative breast cancer. Colloids and Surfaces B: Biointerfaces 2023, 222 , 113094. https://doi.org/10.1016/j.colsurfb.2022.113094
Archit Datar, Qiang Lyu, Li‐Chiang Lin. Machine Learning‐Aided Discovery of Nanoporous Materials for Energy‐ and Environmental‐Related Applications. 2023, 283-318. https://doi.org/10.1002/9781119819783.ch11
Aurelia Li, Rocio Bueno‐Perez, David Fairen‐Jimenez. Extracting Metal‐Organic Frameworks Data from the Cambridge Structural Database. 2023, 201-232. https://doi.org/10.1002/9781119819783.ch8
Reza Maleki, Seyed Mohammadreza Shams, Yasin Mehdizadeh Chellehbari, Sima Rezvantalab, Ahmad Miri Jahromi, Mohsen Asadnia, Rouzbeh Abbassi, Tejraj Aminabhavi, Amir Razmjou. Materials discovery of ion-selective membranes using artificial intelligence. Communications Chemistry 2022, 5 (1) https://doi.org/10.1038/s42004-022-00744-x
Xiangyu Yin, Chrysanthos E. Gounaris. Computational discovery of Metal–Organic Frameworks for sustainable energy systems: Open challenges. Computers & Chemical Engineering 2022, 167 , 108022. https://doi.org/10.1016/j.compchemeng.2022.108022
Hongjian Tang, Jianwen Jiang. Active learning boosted computational discovery of covalent–organic frameworks for ultrahigh CH 4 storage. AIChE Journal 2022, 68 (11) https://doi.org/10.1002/aic.17856
Cigdem Altintas, Ilknur Erucar, Seda Keskin. MOF/COF hybrids as next generation materials for energy and biomedical applications. CrystEngComm 2022, 24 (42) , 7360-7371. https://doi.org/10.1039/D2CE01296K
Gokhan Onder Aksu, Ilknur Erucar, Zeynep Pinar Haslak, Seda Keskin. Exploring covalent organic frameworks for H2S+CO2 separation from natural gas using efficient computational approaches. Journal of CO2 Utilization 2022, 62 , 102077. https://doi.org/10.1016/j.jcou.2022.102077
Christopher Kessler, Robin Schuldt, Sebastian Emmerling, Bettina V. Lotsch, Johannes Kästner, Joachim Gross, Niels Hansen. Influence of layer slipping on adsorption of light gases in covalent organic frameworks: A combined experimental and computational study. Microporous and Mesoporous Materials 2022, 336 , 111796. https://doi.org/10.1016/j.micromeso.2022.111796
Idelfonso B.R. Nogueira, Rafael O.M. Dias, Carine M. Rebello, Erbet A. Costa, Vinicius V. Santana, Alírio E. Rodrigues, Alexandre Ferreira, Ana M. Ribeiro. A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization. Chemical Engineering Research and Design 2022, 180 , 243-253. https://doi.org/10.1016/j.cherd.2022.02.013
Qinglang Ma, Teng Zhang, Bo Wang. Shaping of metal-organic frameworks, a critical step toward industrial applications. Matter 2022, 5 (4) , 1070-1091. https://doi.org/10.1016/j.matt.2022.02.014
Morgan Stefik. Single-variable porous nanomaterial series from polymer structure-directing agents. Journal of Materials Research 2022, 37 (1) , 25-42. https://doi.org/10.1557/s43578-021-00421-0
Gokhan Onder Aksu, Ilknur Erucar, Zeynep Pinar Haslak, Seda Keskin. Accelerating discovery of COFs for CO2 capture and H2 purification using structurally guided computational screening. Chemical Engineering Journal 2022, 427 , 131574. https://doi.org/10.1016/j.cej.2021.131574
Idelfonso B.R. Nogueira, Rafael O.M. Dias, José M. Loureiro, Alírio E. Rodrigues, Alexandre Ferreira, Ana M. Ribeiro. A novel optimization approach for material screening in the adsorption process separation context based on rigorous models: Separation of a mixture of N2 and CO2 in a Pressure Swing Adsorption Unit as a case study. IFAC-PapersOnLine 2022, 55 (20) , 211-216. https://doi.org/10.1016/j.ifacol.2022.09.097
Jaehoon Cha, Seongbin Ga, Seung-jun Lee, Soomyung Nam, Youn-Sang Bae, Yongchul G. Chung. Integrated material and process evaluation of metal–organic frameworks database for energy-efficient SF 6 /N 2 separation. Chemical Engineering Journal 2021, 426 , 131787. https://doi.org/10.1016/j.cej.2021.131787
Ralph Freund, Stefano Canossa, Seth M. Cohen, Wei Yan, Hexiang Deng, Vincent Guillerm, Mohamed Eddaoudi, David G. Madden, David Fairen‐Jimenez, Hao Lyu, Lauren K. Macreadie, Zhe Ji, Yuanyuan Zhang, Bo Wang, Frederik Haase, Christof Wöll, Orysia Zaremba, Jacopo Andreo, Stefan Wuttke, Christian S. Diercks. 25 Years of Reticular Chemistry. Angewandte Chemie International Edition 2021, 60 (45) , 23946-23974. https://doi.org/10.1002/anie.202101644
Ralph Freund, Orysia Zaremba, Giel Arnauts, Rob Ameloot, Grigorii Skorupskii, Mircea Dincă, Anastasiya Bavykina, Jorge Gascon, Aleksander Ejsmont, Joanna Goscianska, Markus Kalmutzki, Ulrich Lächelt, Evelyn Ploetz, Christian S. Diercks, Stefan Wuttke. The Current Status of MOF and COF Applications. Angewandte Chemie International Edition 2021, 60 (45) , 23975-24001. https://doi.org/10.1002/anie.202106259
Ralph Freund, Stefano Canossa, Seth M. Cohen, Wei Yan, Hexiang Deng, Vincent Guillerm, Mohamed Eddaoudi, David G. Madden, David Fairen‐Jimenez, Hao Lyu, Lauren K. Macreadie, Zhe Ji, Yuanyuan Zhang, Bo Wang, Frederik Haase, Christof Wöll, Orysia Zaremba, Jacopo Andreo, Stefan Wuttke, Christian S. Diercks. 25 Jahre retikuläre Chemie. Angewandte Chemie 2021, 133 (45) , 24142-24173. https://doi.org/10.1002/ange.202101644
Ralph Freund, Orysia Zaremba, Giel Arnauts, Rob Ameloot, Grigorii Skorupskii, Mircea Dincă, Anastasiya Bavykina, Jorge Gascon, Aleksander Ejsmont, Joanna Goscianska, Markus Kalmutzki, Ulrich Lächelt, Evelyn Ploetz, Christian S. Diercks, Stefan Wuttke. Der derzeitige Stand von MOF‐ und COF‐Anwendungen. Angewandte Chemie 2021, 133 (45) , 24174-24202. https://doi.org/10.1002/ange.202106259
Marco Taddei, Camille Petit. Engineering metal–organic frameworks for adsorption-based gas separations: from process to atomic scale. Molecular Systems Design & Engineering 2021, 6 (11) , 841-875. https://doi.org/10.1039/D1ME00085C
Christopher Kessler, Johannes Eller, Joachim Gross, Niels Hansen. Adsorption of light gases in covalent organic frameworks: comparison of classical density functional theory and grand canonical Monte Carlo simulations. Microporous and Mesoporous Materials 2021, 324 , 111263. https://doi.org/10.1016/j.micromeso.2021.111263
Hilal Daglar, Ilknur Erucar, Seda Keskin. Recent advances in simulating gas permeation through MOF membranes. Materials Advances 2021, 2 (16) , 5300-5317. https://doi.org/10.1039/D1MA00026H
Lukas Turcani, Andrew Tarzia, Filip T. Szczypiński, Kim E. Jelfs. stk : An extendable Python framework for automated molecular and supramolecular structure assembly and discovery. The Journal of Chemical Physics 2021, 154 (21) https://doi.org/10.1063/5.0049708
Mohammad Rahimi, Seyed Mohamad Moosavi, Berend Smit, T. Alan Hatton. Toward smart carbon capture with machine learning. Cell Reports Physical Science 2021, 2 (4) , 100396. https://doi.org/10.1016/j.xcrp.2021.100396
Hilal Daglar, Hasan Can Gulbalkan, Gokay Avci, Gokhan Onder Aksu, Omer Faruk Altundal, Cigdem Altintas, Ilknur Erucar, Seda Keskin. Effect of Metal–Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs. Angewandte Chemie 2021, 133 (14) , 7907-7916. https://doi.org/10.1002/ange.202015250
Hilal Daglar, Hasan Can Gulbalkan, Gokay Avci, Gokhan Onder Aksu, Omer Faruk Altundal, Cigdem Altintas, Ilknur Erucar, Seda Keskin. Effect of Metal–Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs. Angewandte Chemie International Edition 2021, 60 (14) , 7828-7837. https://doi.org/10.1002/anie.202015250
Kevin Maik Jablonka, Seyed Mohamad Moosavi, Mehrdad Asgari, Christopher Ireland, Luc Patiny, Berend Smit. A data-driven perspective on the colours of metal–organic frameworks. Chemical Science 2021, 12 (10) , 3587-3598. https://doi.org/10.1039/D0SC05337F
Caroline Desgranges, Jerome Delhommelle. Towards a machine learned thermodynamics: exploration of free energy landscapes in molecular fluids, biological systems and for gas storage and separation in metal–organic frameworks. Molecular Systems Design & Engineering 2021, 6 (1) , 52-65. https://doi.org/10.1039/D0ME00134A
Eva Martínez-Ahumada, Mariana L. Díaz-Ramírez, Miriam de J. Velásquez-Hernández, Vojtech Jancik, Ilich A. Ibarra. Capture of toxic gases in MOFs: SO 2 , H 2 S, NH 3 and NO x. Chemical Science 2021, 7 https://doi.org/10.1039/D1SC01609A
Maria João Regufe, Vinícius V. Santana, Márcio M. Martins, Alexandre F.P. Ferreira, José M. Loureiro, Alírio E. Rodrigues, Ana M. Ribeiro, Idelfonso B.R. Nogueira. Adsorption material composition and process optimization, a systematical approach based on Deep Learning. IFAC-PapersOnLine 2021, 54 (3) , 43-48. https://doi.org/10.1016/j.ifacol.2021.08.216

Download PDF

Abstract
High Resolution Image
Download MS PowerPoint Slide
Figure 1
Figure 1. (a) Papers mentioning “Zeolite”, “Metal Organic Framework”, and “Covalent Organic Framework” in the title or the abstract, as parsed from Scopus in July 2020. (7) The right column collects histograms for the deposition of materials in publicly available databases. (b) Zeolite code types by year of assignment, from the database of the International Zeolite Association (IZA). (8) (c) MOF-subset of the Cambridge Structural Database (CSD, May 20 update) by year of publication (orange). (9) MOFs in the CoRE-2019 “All solvent Removed” (ASR) subset (purple) are selected from the CSD release of November 2017 with criteria such as three-dimensionality of the framework and permeability to small molecules. (10) (d) COFs in the CURATED-COFs database (June 20 update), by year of publication. (11,12)
High Resolution Image
Download MS PowerPoint Slide
Figure 2
Figure 2. Scheme of exemplary workflow. The user starts by uploading the atomic structure of a crystalline materials in the CIF format, which triggers the refinement of the atomic positions, the computation of pore geometry, and thermodynamic and transport properties. Finally, its performance for specific applications is evaluated, and the material is ranked versus other candidates.
High Resolution Image
Download MS PowerPoint Slide
Figure 3
Figure 3. Performance of COF structures for CO₂ capture: parasitic energy required for the process versus gravimetric working capacity. Markers of the 250 new COFs are color-coded based on their ranking from high performance (low parasitic energy and high working capacity, green) to low performance (red). Markers of materials already included in ref (11) are shown in light gray.
High Resolution Image
Download MS PowerPoint Slide
Figure 4
Figure 4. Performance of CURATED-COFs for H₂ storage at (a) cryogenic and (b) near-ambient conditions, (c) methane storage, (d) oxygen storage, (e) Xe/Kr separation, and (f) (H₂S)/water separation. The ranking is color-coded from high performance (green) to low performance (red). Selectivities are computed as the ratio of the Henry coefficients of the two gases at 300 K. The coordinates of the markers for T-COF-2 and JUC-509 are highlighted by dashed and solid lines, respectively.
High Resolution Image
Download MS PowerPoint Slide
Figure 5
Figure 5. AiiDA provenance graph of the workflow tracing the entire path from the initial CIF file to the properties and performance computed for it. The graph shows process and data as nodes, and their connection: (49) in an interactive visualization, each node can be browsed to explore the input parameters of the calculation, its output results, and the details of the processes. (104) Colors distinguish different modules of the workflow, whose source code is available online. (90) The modules make use of other popular open-source tools, such as CP2K, (105) Raspa, (106) Zeo++, (66) and chargemol. (107)
High Resolution Image
Download MS PowerPoint Slide
Figure 6
Figure 6. Crystal structures of (a) T-COF-2 and (b) JUC-509. Elements: H (white), C (gray), N (blue), oxygen (red), S (yellow), Cl (green).
High Resolution Image
Download MS PowerPoint Slide
References
ARTICLE SECTIONS
Jump To
This article references 110 other publications.
1. 1
  Wang, C.; Wang, Y.; Ge, R.; Song, X.; Xing, X.; Jiang, Q.; Lu, H.; Hao, C.; Guo, X.; Gao, Y.; Jiang, D. A 3D covalent organic framework with exceptionally high iodine capture capability. Chem. - Eur. J. 2018, 24, 585– 589, DOI: 10.1002/chem.201705405
  [Crossref], [PubMed], [CAS], Google Scholar
  1
  A 3D Covalent Organic Framework with Exceptionally High Iodine Capture Capability
  Wang, Chang; Wang, Yu; Ge, Rile; Song, Xuedan; Xing, Xueqing; Jiang, Qike; Lu, Hui; Hao, Ce; Guo, Xinwen; Gao, Yanan; Jiang, Donglin
  Chemistry - A European Journal (2018), 24 (3), 585-589CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)
  Using porous materials to cope with environmental issues is promising but remains a challenge esp. for removing the radioactive vapor wastes in fission because of harsh adsorption conditions. Here we report a new, stable covalent org. framework (COF) as a porous platform for removing iodine vapor-a major radioactive fission waste. The three-dimensional COF consists of a diamond topol. knotted by adamantane units, creates ordered one-dimensional pores and are highly porous. The COF enables the removal of iodine vapor via charge transfer complex formation with the pore walls to achieve exceptional capacity. Moreover, the 3D COF is "soft" to trigger structural fitting to iodine while retaining connectivity and enables cycle use for many times while retaining high uptake capacity. These results set a new benchmark for fission waste removal and suggest the great potential of COFs as a designable porous material for challenging world-threatening pollution issues.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhvFyjsbbE&md5=3e09a97792181c87badfdf7f38d4d39d
2. 2
  Mason, J. A.; Veenstra, M.; Long, J. R. Evaluating metal–organic frameworks for natural gas storage. Chem. Sci. 2014, 5, 32– 51, DOI: 10.1039/C3SC52633J
  [Crossref], [CAS], Google Scholar
  2
  Evaluating metal-organic frameworks for natural gas storage
  Mason, Jarad A.; Veenstra, Mike; Long, Jeffrey R.
  Chemical Science (2014), 5 (1), 32-51CODEN: CSHCCN; ISSN:2041-6520. (Royal Society of Chemistry)
  Metal-org. frameworks have received significant attention as a new class of adsorbents for natural gas storage; however, inconsistencies in reporting high-pressure adsorption data and a lack of comparative studies have made it challenging to evaluate both new and existing materials. Here, we briefly discuss high-pressure adsorption measurements and review efforts to develop metal-org. frameworks with high methane storage capacities. To illustrate the most important properties for evaluating adsorbents for natural gas storage and for designing a next generation of improved materials, six metal-org. frameworks and an activated carbon, with a range of surface areas, pore structures, and surface chemistries representative of the most promising adsorbents for methane storage, are evaluated in detail. High-pressure methane adsorption isotherms are used to compare gravimetric and volumetric capacities, isosteric heats of adsorption, and usable storage capacities. Addnl., the relative importance of increasing volumetric capacity, rather than gravimetric capacity, for extending the driving range of natural gas vehicles is highlighted. Other important systems-level factors, such as thermal management, mech. properties, and the effects of impurities, are also considered, and potential materials synthesis contributions to improving performance in a complete adsorbed natural gas system are discussed.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVGntLvE&md5=05a99cd7be9ef1819aca42d1c36f1f1d
3. 3
  Zhu, L.; Liu, X.-Q.; Jiang, H.-L.; Sun, L.-B. Metal–Organic Frameworks for Heterogeneous Basic Catalysis. Chem. Rev. 2017, 117, 8129, DOI: 10.1021/acs.chemrev.7b00091
  [ACS Full Text ], [CAS], Google Scholar
  3
  Metal-Organic Frameworks for Heterogeneous Basic Catalysis
  Zhu, Li; Liu, Xiao-Qin; Jiang, Hai-Long; Sun, Lin-Bing
  Chemical Reviews (Washington, DC, United States) (2017), 117 (12), 8129-8176CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. Great attention has been given to metal-org. frameworks (MOFs)-derived solid bases because of their attractive structure and catalytic performance in various org. reactions. The extraordinary skeleton structure of MOFs provides many possibilities for incorporation of diverse basic functionalities, which is unachievable for conventional solid bases. The past decade has witnessed remarkable advances in this vibrant research area; however, MOFs for heterogeneous basic catalysis have never been reviewed until now. Therefore, a review summarizing MOFs-derived base catalysts is highly expected. In this review, we present an overview of the recent progress in MOFs-derived solid bases covering prepn., characterization, and catalytic applications. In the prepn. section, the solid bases are divided into two categories, namely, MOFs with intrinsic basicity and MOFs with modified basicity. The basicity can originate from either metal sites or org. ligands. Different approaches used for generation of basic sites are included, and each approach is described with representative examples. The fundamental principles for the design and fabrication of MOFs with basic functionalities are featured. In the characterization section, exptl. techniques and theor. calcns. employed for characterization of basic MOFs are summarized. Some representive exptl. techniques, such as temp.-programmed desorption of CO2 (CO2-TPD) and IR (IR) spectra of different probing mols., are covered. Following prepn. and characterization, the catalytic applications of MOFs-derived solid bases are dealt with. These solid bases have potential to catalyze some well-known "base-catalyzed reactions" like Knoevenagel condensation, aldol condensation, and Michael addn. Meanwhile, in contrast to conventional solid bases, MOFs show some different catalytic properties due to their special structural and surface properties. Remarkably, characteristic features of MOFs-derived solid bases are described by comparing with conventional inorg. counterparts, keeping in mind the current opportunities and challenges in this field.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXotlaku7o%253D&md5=b4be0fef2c9454a53492290865537878
4. 4
  Bavykina, A.; Kolobov, N.; Khan, I. S.; Bau, J. A.; Ramirez, A.; Gascon, J. Metal–Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives. Chem. Rev. 2020, 120, 8468, DOI: 10.1021/acs.chemrev.9b00685
  [ACS Full Text ], [CAS], Google Scholar
  4
  Metal-Organic Frameworks in Heterogeneous Catalysis: Recent Progress, New Trends, and Future Perspectives
  Bavykina, Anastasiya; Kolobov, Nikita; Khan, Il Son; Bau, Jeremy A.; Ramirez, Adrian; Gascon, Jorge
  Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8468-8535CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. More than 95% (in vol.) of all of today's chem. products are manufd. through catalytic processes, making research into more efficient catalytic materials a thrilling and very dynamic research field. In this regard, metal-org. frameworks (MOFs) offer great opportunities for the rational design of new catalytic solids, as highlighted by the unprecedented no. of publications appearing over the past decade. In this review, the recent advances in the application of MOFs in heterogeneous catalysis are discussed. MOFs with intrinsic thermocatalytic activity, as hosts for the incorporation of metal nanoparticles, as precursors for the manuf. of composite catalysts and those active in photo- and electrocatalytic processes are critically reviewed. The review is wrapped up with our personal view on future research directions.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlslOns7o%253D&md5=857333854eb405b199bd222354bd6218
5. 5
  Liu, X.; Huang, D.; Lai, C.; Zeng, G.; Qin, L.; Wang, H.; Yi, H.; Li, B.; Liu, S.; Zhang, M.; Deng, R.; Fu, Y.; Li, L.; Xue, W.; Chen, S. Recent advances in covalent organic frameworks (COFs) as a smart sensing material. Chem. Soc. Rev. 2019, 48, 5266– 5302, DOI: 10.1039/C9CS00299E
  [Crossref], [PubMed], [CAS], Google Scholar
  5
  Recent advances in covalent organic frameworks (COFs) as a smart sensing material
  Liu, Xigui; Huang, Danlian; Lai, Cui; Zeng, Guangming; Qin, Lei; Wang, Han; Yi, Huan; Li, Bisheng; Liu, Shiyu; Zhang, Mingming; Deng, Rui; Fu, Yukui; Li, Ling; Xue, Wenjing; Chen, Sha
  Chemical Society Reviews (2019), 48 (20), 5266-5302CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
  A review. As a newly emerging kind of porous material, covalent org. frameworks (COFs) have drawn much attention because of their fascinating structural features (e.g., divinable structure, adjustable porosity and total org. backbone). Since the seminal work of Yaghi and co-workers reported in 2005, the COF materials have shown superior potential in diverse applications, such as gas storage, adsorption, optoelectronics, catalysis, etc. Recently, COF materials have shown a new trend in sensing fields. This crit. review briefly describes the synthesis routes for COF powders and thin films. What's more, the most fascinating and significant applications of COFs in sensing fields including explosive sensing, humidity sensing, pH detection, biosensing, gas sensing, metal ion sensing, and other substance sensing are summarized and highlighted. Finally, the major challenges and future trends of COFs with respect to their prepn. and sensing applications are discussed.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1Oms7zM&md5=3bf2091e122fdc08d3e757c4d0ea5f77
6. 6
  Kreno, L. E.; Leong, K.; Farha, O. K.; Allendorf, M.; Van Duyne, R. P.; Hupp, J. T. Metal–Organic Framework Materials as Chemical Sensors. Chem. Rev. 2012, 112, 1105– 1125, DOI: 10.1021/cr200324t
  [ACS Full Text ], [CAS], Google Scholar
  6
  Metal-Organic Framework Materials as Chemical Sensors
  Kreno, Lauren E.; Leong, Kirsty; Farha, Omar K.; Allendorf, Mark; Van Duyne, Richard P.; Hupp, Joseph T.
  Chemical Reviews (Washington, DC, United States) (2012), 112 (2), 1105-1125CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. The authors present a crit. review of the literature on metal-org. frameworks (MOFs) as chem. sensors. The authors begin by briefly examg. challenges relating to MOF sensor development including the design of MOFs with desirable properties, incorporation of appropriate signal transduction capabilities, and integration of MOFs into devices by employing thin-film growth techniques. Subsequent sections discuss specific examples of MOF sensors, categorized by method of signal transduction. Sensors based on MOF photoluminescence are discussed briefly. The authors have limited the review of luminescence-based sensors to a small no. of recent reports where the porous MOF architecture, or its chem. compn., imparts selective sensing capabilities. Scintillating MOFs that luminesce in the presence of radioactive analytes are also discussed. Other signal transduction schemes that use photons include various kinds of optical interferometry, analyte modulation of localized surface plasmon resonance energies, and solvatochromism. Mech. signal-transduction schemes employed with MOFs include ones based on surface acoustic wave, quartz crystal microbalance, and microcantilever devices. Elec. schemes thus far were limited to ones based on impedance spectroscopy.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVCgtL%252FI&md5=f6ed572725bc067ee8da81880bf1ec90
7. 7
  Burnham, J. F. Scopus database: a review. Biomed. Digit. Libr. 2006, 3, 1, DOI: 10.1186/1742-5581-3-1
  [Crossref], [PubMed], [CAS], Google Scholar
  7
  Scopus database: a review
  Burnham Judy F
  Biomedical digital libraries (2006), 3 (), 1 ISSN:.
  The Scopus database provides access to STM journal articles and the references included in those articles, allowing the searcher to search both forward and backward in time. The database can be used for collection development as well as for research. This review provides information on the key points of the database and compares it to Web of Science. Neither database is inclusive, but complements each other. If a library can only afford one, choice must be based in institutional needs.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD287nslKmsg%253D%253D&md5=e20a31e5cc40dca57d9087b9ed529da0
8. 8
  Database of Zeolite Structures. www.iza-structure.org/databases/ (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
9. 9
  Moghadam, P. Z.; Li, A.; Wiggin, S. B.; Tao, A.; Maloney, A. G. P.; Wood, P. A.; Ward, S. C.; Fairen-Jimenez, D. Development of a Cambridge structural database subset: a collection of metal-organic frameworks for past, present, and future. Chem. Mater. 2017, 29, 2618– 2625, DOI: 10.1021/acs.chemmater.7b00441
  [ACS Full Text ], [CAS], Google Scholar
  9
  Development of a Cambridge Structural Database Subset: A Collection of Metal-Organic Frameworks for Past, Present, and Future
  Moghadam, Peyman Z.; Li, Aurelia; Wiggin, Seth B.; Tao, Andi; Maloney, Andrew G. P.; Wood, Peter A.; Ward, Suzanna C.; Fairen-Jimenez, David
  Chemistry of Materials (2017), 29 (7), 2618-2625CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  The generation and characterization of the most complete collection of metal-org. frameworks (MOFs) maintained and updated by the Cambridge Crystallog. Data Center (CCDC) is reported. To set up this subset, the question was asked what is a MOF and a no. of look-for-MOF criteria embedded within a bespoke Cambridge Structural Database (CSD) Python API workflow was implemented to identify and ext. information on 69,666 MOF materials. The CSD MOF subset is updated regularly with subsequent MOF addns. to the CSD, bringing a unique record for all researchers working in the area of porous materials around the world, whether to perform high-throughput computational screening for materials discovery or to have a global view over the existing structures in a single resource. Using this resource, the authors then developed and used an array of computational tools to remove residual solvent mols. from the framework pores of all the MOFs identified and went on to analyze geometrical and phys. properties of nondisordered structures.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXkt12rurc%253D&md5=377ebf2d805518194eb8cd0f9d3f3608
10. 10
  Chung, Y. G.; Haldoupis, E.; Bucior, B. J.; Haranczyk, M.; Lee, S.; Zhang, H.; Vogiatzis, K. D.; Milisavljevic, M.; Ling, S.; Camp, J. S.; Slater, B.; Siepmann, J. I.; Sholl, D. S.; Snurr, R. Q. Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019. J. Chem. Eng. Data 2019, 64, 5985– 5998, DOI: 10.1021/acs.jced.9b00835
  [ACS Full Text ], [CAS], Google Scholar
  10
  Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal-Organic Framework Database: CoRE MOF 2019
  Chung, Yongchul G.; Haldoupis, Emmanuel; Bucior, Benjamin J.; Haranczyk, Maciej; Lee, Seulchan; Zhang, Hongda; Vogiatzis, Konstantinos D.; Milisavljevic, Marija; Ling, Sanliang; Camp, Jeffrey S.; Slater, Ben; Siepmann, J. Ilja; Sholl, David S.; Snurr, Randall Q.
  Journal of Chemical & Engineering Data (2019), 64 (12), 5985-5998CODEN: JCEAAX; ISSN:0021-9568. (American Chemical Society)
  Over 14 000 porous, three-dimensional metal-org. framework structures are compiled and analyzed as a part of an update to the Computation-Ready, Exptl. Metal-Org. Framework Database (CoRE MOF Database). The updated database includes addnl. structures that were contributed by CoRE MOF users, obtained from updates of the Cambridge Structural Database and a Web of Science search, and derived through semiautomated reconstruction of disordered structures using a topol.-based crystal generator. In addn., value is added to the CoRE MOF database through new analyses that can speed up future nanoporous materials discovery activities, including open metal site detection and duplicate searches. Crystal structures (only for the subset that underwent significant changes during curation), pore analytics, and phys. property data are included with the publicly available CoRE MOF 2019 database.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitVOmtrrL&md5=51670c93eb8cb43309395afaaf620253
11. 11
  Ongari, D.; Yakutovich, A. V.; Talirz, L.; Smit, B. Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent–Organic Frameworks. ACS Cent. Sci. 2019, 5, 1663– 1675, DOI: 10.1021/acscentsci.9b00619
  [ACS Full Text ], [CAS], Google Scholar
  11
  Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent-Organic Frameworks
  Ongari, Daniele; Yakutovich, Aliaksandr V.; Talirz, Leopold; Smit, Berend
  ACS Central Science (2019), 5 (10), 1663-1675CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
  We present a workflow that traces the path from the bulk structure of a cryst. material to assessing its performance in carbon capture from coal's postcombustion flue gases. This workflow is applied to a database of 324 covalent-org. frameworks (COFs) reported in the literature, to characterize their CO2 adsorption properties using the following steps: (1) optimization of the crystal structure (at. positions and unit cell) using d. functional theory, (2) fitting at. point charges based on the electron d., (3) characterizing the pore geometry of the structures before and after optimization, (4) computing carbon dioxide and nitrogen isotherms using grand canonical Monte Carlo simulations with an empirical interaction potential, and finally, (5) assessing the CO2 parasitic energy via process modeling. The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA). Both the workflow and the automatically generated provenance graph of our calcns. are made available on the Materials Cloud, allowing peers to inspect every input parameter and result along the workflow, download structures and files at intermediate stages, and start their research right from where this work has left off. In particular, our set of CURATED (Clean, Uniform, and Refined with Automatic Tracking from Exptl. Database) COFs, having optimized geometry and high-quality DFT-derived point charges, are available for further investigations of gas adsorption properties. We plan to update the database as new COFs are being reported. An automated and reproducible computational workflow is proposed, to systematically optimize the geometry of covalent-org. frameworks and evaluate their performances for carbon capture and storage.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvVeqsL%252FM&md5=8f47a5e3d00532e7064d5259e73ab1f1
12. 12
  CURATED-COFs. github.com/danieleongari/egulp (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
13. 13
  Boyd, P. G. Data-driven design of metal–organic frameworks for wet flue gas CO2 capture. Nature 2019, 576, 253– 256, DOI: 10.1038/s41586-019-1798-7
  [Crossref], [PubMed], [CAS], Google Scholar
  13
  Data-driven design of metal-organic frameworks for wet flue gas CO2 capture
  Boyd, Peter G.; Chidambaram, Arunraj; Garcia-Diez, Enrique; Ireland, Christopher P.; Daff, Thomas D.; Bounds, Richard; Gladysiak, Andrzej; Schouwink, Pascal; Moosavi, Seyed Mohamad; Maroto-Valer, M. Mercedes; Reimer, Jeffrey A.; Navarro, Jorge A. R.; Woo, Tom K.; Garcia, Susana; Stylianou, Kyriakos C.; Smit, Berend
  Nature (London, United Kingdom) (2019), 576 (7786), 253-256CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
  Limiting the increase of CO2 in the atm. is one of the largest challenges of our generation1. Because carbon capture and storage is one of the few viable technologies that can mitigate current CO2 emissions2, much effort is focused on developing solid adsorbents that can efficiently capture CO2 from flue gases emitted from anthropogenic sources3. One class of materials that has attracted considerable interest in this context is metal-org. frameworks (MOFs), in which the careful combination of org. ligands with metal-ion nodes can, in principle, give rise to innumerable structurally and chem. distinct nanoporous MOFs. However, many MOFs that are optimized for the sepn. of CO2 from nitrogen4-7 do not perform well when using realistic flue gas that contains water, because water competes with CO2 for the same adsorption sites and thereby causes the materials to lose their selectivity. Although flue gases can be dried, this renders the capture process prohibitively expensive8,9. Here we show that data mining of a computational screening library of over 300,000 MOFs can identify different classes of strong CO2-binding sites-which we term 'adsorbaphores'-that endow MOFs with CO2/N2 selectivity that persists in wet flue gases. We subsequently synthesized two water-stable MOFs contg. the most hydrophobic adsorbaphore, and found that their carbon-capture performance is not affected by water and outperforms that of some com. materials. Testing the performance of these MOFs in an industrial setting and consideration of the full capture process-including the targeted CO2 sink, such as geol. storage or serving as a carbon source for the chem. industry-will be necessary to identify the optimal sepn. material.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitlOmu7zN&md5=ed26245f884c2d2fa86f6d4251be593a
14. 14
  Banerjee, D.; Simon, C. M.; Plonka, A. M.; Motkuri, R. K.; Liu, J.; Chen, X.; Smit, B.; Parise, J. B.; Haranczyk, M.; Thallapally, P. K. Metal–organic framework with optimally selective xenon adsorption and separation. Nat. Commun. 2016, 7, 11831, DOI: 10.1038/ncomms11831
  [Crossref], [CAS], Google Scholar
  14
  Metal-organic framework with optimally selective xenon adsorption and separation
  Banerjee, Debasis; Simon, Cory M.; Plonka, Anna M.; Motkuri, Radha K.; Liu, Jian; Chen, Xianyin; Smit, Berend; Parise, John B.; Haranczyk, Maciej; Thallapally, Praveen K.
  Nature Communications (2016), 7 (), ncomms11831CODEN: NCAOBW; ISSN:2041-1723. (Nature Publishing Group)
  Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in ppm concns. The existing technol. to remove these radioactive noble gases is a costly cryogenic distn.; alternatively, porous materials such as metal-org. frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal-org. frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtVSlu7zL&md5=707c333c8eb651e3cd510eb456b5f617
15. 15
  Schnobrich, J. K.; Lebel, O.; Cychosz, K. A.; Dailly, A.; Wong-Foy, A. G.; Matzger, A. J. Linker-Directed Vertex Desymmetrization for the Production of Coordination Polymers with High Porosity. J. Am. Chem. Soc. 2010, 132, 13941– 13948, DOI: 10.1021/ja107423k
  [ACS Full Text ], [CAS], Google Scholar
  15
  Linker-Directed Vertex Desymmetrization for the Production of Coordination Polymers with High Porosity
  Schnobrich, Jennifer K.; Lebel, Olivier; Cychosz, Katie A.; Dailly, Anne; Wong-Foy, Antek G.; Matzger, Adam J.
  Journal of the American Chemical Society (2010), 132 (39), 13941-13948CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  Several noninterpenetrated microporous coordination polymers (MCPs) are derived by vertex desymmetrization using linkers with symmetry inequivalent coordinating groups, and these MCPs include properties such as rare metal clusters, new network topologies, and supramol. isomerism. Gas sorption in polymorphic frameworks, UMCM-152 and UMCM-153 (based upon a Cu-coordinated tetracarboxylated triphenylbenzene linker), reveals nearly identical properties with BET surface areas at 3300-3500 m2/g and excess H uptake of 5.7 and 5.8% at 77 K. In contrast, adsorption of organosulfur compds. dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (DMDBT) shows remarkably different capacities, providing direct evidence that liq.-phase adsorption is not solely dependent on surface area or linker/metal cluster identity. Structural features present in MCPs derived from these reduced symmetry linkers include the presence of more than one type of Cu-paddlewheel in a structure derived from a terphenyl tricarboxylate (UMCM-151) and a three-bladed Zn paddlewheel metal cluster in an MCP derived from a pentacarboxylated triphenylbenzene linker (UMCM-154).
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFKmt7fJ&md5=6df71c877714d682bf6abcff77920e9c
16. 16
  Moghadam, P. Z.; Islamoglu, T.; Goswami, S.; Exley, J.; Fantham, M.; Kaminski, C. F.; Snurr, R. Q.; Farha, O. K.; Fairen-Jimenez, D. Computer-aided discovery of a metal–organic framework with superior oxygen uptake. Nat. Commun. 2018, 9, 1378, DOI: 10.1038/s41467-018-03892-8
  [Crossref], [PubMed], [CAS], Google Scholar
  16
  Computer-aided discovery of a metal-organic framework with superior oxygen uptake
  Moghadam Peyman Z; Fantham Marcus; Kaminski Clemens F; Fairen-Jimenez David; Islamoglu Timur; Goswami Subhadip; Farha Omar K; Exley Jason; Snurr Randall Q; Farha Omar K; Farha Omar K
  Nature communications (2018), 9 (1), 1378 ISSN:.
  Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MjhsFSmuw%253D%253D&md5=1b73eac548f4efca88ba8e47f0eaa1c1
17. 17
  Sturluson, A.; Huynh, M. T.; Kaija, A. R.; Laird, C.; Yoon, S.; Hou, F.; Feng, Z.; Wilmer, C. E.; Colón, Y. J.; Chung, Y. G.; Siderius, D. W.; Simon, C. M. The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation. Mol. Simul. 2019, 45, 1082– 1121, DOI: 10.1080/08927022.2019.1648809
  [Crossref], [CAS], Google Scholar
  17
  The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation†
  Sturluson, Arni; Huynh, Melanie T.; Kaija, Alec R.; Laird, Caleb; Yoon, Sunghyun; Hou, Feier; Feng, Zhenxing; Wilmer, Christopher E.; Colon, Yamil J.; Chung, Yongchul G.; Siderius, Daniel W.; Simon, Cory M.
  Molecular Simulation (2019), 45 (14-15), 1082-1121CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)
  A review. Metal-org. frameworks (MOFs) are highly tuneable, extended-network, cryst., nanoporous materials with applications in gas storage, sepns., and sensing. We review how mol. models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chem. warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable mol. simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhsFChurjJ&md5=d02e6ff3468030ef2f7196f97a3ae863
18. 18
  Boyd, P. G.; Lee, Y.; Smit, B. Computational development of the nanoporous materials genome. Nat. Rev. Mater. 2017, 2, 17037, DOI: 10.1038/natrevmats.2017.37
  [Crossref], [CAS], Google Scholar
  18
  Computational development of the nanoporous materials genome
  Boyd, Peter G.; Lee, Yongjin; Smit, Berend
  Nature Reviews Materials (2017), 2 (2), 17037CODEN: NRMADL; ISSN:2058-8437. (Nature Publishing Group)
  A review. There is currently a push towards big data and data mining in materials research to accelerate discovery. Zeolites, metal-org. frameworks and other related cryst. porous materials are not immune to this phenomenon, as evidenced by the proliferation of porous structure databases and computational gas-adsorption screening studies over the past decade. The endeavour to identify the best materials for various gas sepn. and storage applications has led not only to thousands of synthesized structures, but also to the development of algorithms for building hypothetical materials. The materials databases assembled with these algorithms contain a much wider range of complex pore structures than have been synthesized, with the reasoning being that we have discovered only a small fraction of realizable structures and expanding upon these will accelerate rational design. In this Review, we highlight the methods developed to build these databases, and some of the important outcomes from large-scale computational screening studies.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtFegt7bI&md5=9c113afa97107e12fa266a20143d5627
19. 19
  Mancuso, J. L.; Mroz, A. M.; Le, K. N.; Hendon, C. H. Electronic Structure Modeling of Metal–Organic Frameworks. Chem. Rev. 2020, 120, 8641, DOI: 10.1021/acs.chemrev.0c00148
  [ACS Full Text ], [CAS], Google Scholar
  19
  Electronic Structure Modeling of Metal-Organic Frameworks
  Mancuso, JennaL.; Mroz, Austin M.; Le, Khoa N.; Hendon, Christopher H.
  Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8641-8715CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. Owing to their mol. building blocks, yet highly cryst. nature, metal-org. frameworks (MOFs) sit at the interface between mol. and material. Their diverse structures and compns. enable them to be useful materials as catalysts in heterogeneous reactions, elec. conductors in energy storage and transfer applications, chromophores in photoenabled chem. transformations, and beyond. In all cases, d. functional theory (DFT) and higher-level methods for electronic structure detn. provide valuable quant. information about the electronic properties that underpin the functions of these frameworks. However, there are only two general modeling approaches in conventional electronic structure software packages: those that treat materials as extended, periodic solids, and those that treat materials as discrete mols. Each approach has features and benefits; both have been widely employed to understand the emergent chem. that arises from the formation of the metal-org. interface. This Review canvases these approaches to date, with emphasis placed on the application of electronic structure theory to explore reactivity and electron transfer using periodic, mol., and embedded models. This includes (i) computational chem. considerations such as how functional, k-grid, and other model variables are selected to enable insights into MOF properties, (ii) extended solid models that treat MOFs as materials rather than mols., (iii) the mechanics of cluster extn. and subsequent chem. enabled by these mol. models, (iv) catalytic studies using both solids and clusters thereof, and (v) embedded, mixed-method approaches, which simulate a fraction of the material using one level of theory and the remainder of the material using another dissimilar theor. implementation.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlymurvP&md5=2776969588b29b0185b24eede1f5e87a
20. 20
  Tan, J.-C.; Civalleri, B.; Erba, A.; Albanese, E. Quantum mechanical predictions to elucidate the anisotropic elastic properties of zeolitic imidazolate frameworks: ZIF-4 vs. ZIF-zni. CrystEngComm 2015, 17, 375– 382, DOI: 10.1039/C4CE01564A
  [Crossref], [CAS], Google Scholar
  20
  Quantum mechanical predictions to elucidate the anisotropic elastic properties of zeolitic imidazolate frameworks: ZIF-4 vs. ZIF-zni
  Tan, Jin-Chong; Civalleri, Bartolomeo; Erba, Alessandro; Albanese, Elisa
  CrystEngComm (2015), 17 (2), 375-382CODEN: CRECF4; ISSN:1466-8033. (Royal Society of Chemistry)
  We use ab initio d. functional theory (DFT) to elucidate the mech. properties of two topol. distinct zeolitic imidazolate framework (ZIF) materials: ZIF-4 and ZIF-zni, both of which have the same chem. compn. of Zn(Im)2 [Im = C3H3N2-] and are constructed from an identical Zn-Im-Zn basic building block. The CRYSTAL code was used to compute the single-crystal elastic consts. Cij of the (orthorhombic) ZIF-4 and (tetragonal) ZIF-zni structures at the PBE level of theory. Through tensorial anal. of the Cij, we reveal the three-dimensional representation surfaces of the Young's modulus, shear modulus, Poisson's ratio and linear compressibility, which enable us to describe the detailed elasticity behavior and to pinpoint basic crystal structure-property correlations. Notably, we discover that ZIF-4 can potentially exhibit a neg. Poisson's ratio, thereby representing the first example of an 'auxetic-ZIF' to be identified to date. Furthermore, we show that our DFT predictions are consistent with recently reported exptl. measurements of the Young's and bulk moduli of such complex ZIF structures.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVCjtLbN&md5=2efbd43f987a1e0271ff079702b0ec31
21. 21
  Ryder, M. R.; Maul, J.; Civalleri, B.; Erba, A. Quasi-Harmonic Lattice Dynamics of a Prototypical Metal–Organic Framework. Adv. Theory Simulations 2019, 2, 1900093, DOI: 10.1002/adts.201900093
  [Crossref], [CAS], Google Scholar
  21
  Quasi-Harmonic Lattice Dynamics of a Prototypical Metal-Organic Framework
  Ryder, Matthew R.; Maul, Jefferson; Civalleri, Bartolomeo; Erba, Alessandro
  Advanced Theory and Simulations (2019), 2 (11), 1900093CODEN: ATSDCW; ISSN:2513-0390. (Wiley-VCH Verlag GmbH & Co. KGaA)
  Quasi-harmonic lattice-dynamical calcns. are performed to investigate the combined effect of temp. and pressure on the structural and mech. properties of a prototypical metal-org. framework material: MOF-5. The softening upon compression of an A2g phonon mode at the Γ point in the high-symmetry Fm3m structure is identified, which leads to a symmetry redn. and a group-subgroup phase transition to a low-symmetry Fm3 phase for compressions larger than 0.8%. The effect of the symmetry redn. on the equation-of-state of MOF-5 is investigated, which provides a static bulk modulus K reducing from 17 to 14 GPa and a corresponding change of K' (pressure deriv. of K) from pos. to neg. The effect of pressure on the neg. thermal expansion of the framework and on its mech. response is analyzed. The evolution of the mech. anisotropy of MOF-5 as a function of pressure is also detd., which allows identifying the occurrence of a shear-induced mech. instability at 0.45 GPa.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXitlyjsbvP&md5=0a8ccfdd89deed22ec740a7eaf2900f0
22. 22
  Bernales, V.; Ortuño, M. A.; Truhlar, D. G.; Cramer, C. J.; Gagliardi, L. Computational Design of Functionalized Metal–Organic Framework Nodes for Catalysis. ACS Cent. Sci. 2018, 4, 5– 19, DOI: 10.1021/acscentsci.7b00500
  [ACS Full Text ], [CAS], Google Scholar
  22
  Computational Design of Functionalized Metal-Organic Framework Nodes for Catalysis
  Bernales, Varinia; Ortuno, Manuel A.; Truhlar, Donald G.; Cramer, Christopher J.; Gagliardi, Laura
  ACS Central Science (2018), 4 (1), 5-19CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
  A review; recent progress in the synthesis and characterization of metal-org. frameworks (MOFs) has opened the door to an increasing no. of possible catalytic applications. The great versatility of MOFs creates a large chem. space, whose thorough exptl. examn. becomes practically impossible. Therefore, computational modeling is a key tool to support, rationalize, and guide exptl. efforts. In this outlook we survey the main methodologies employed to model MOFs for catalysis, and we review selected recent studies on the functionalization of their nodes. We pay special attention to catalytic applications involving natural gas conversion.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXitVShtLfN&md5=f706f2bdf686fc3334f1bc63a07290d7
23. 23
  Rosen, A. S.; Notestein, J. M.; Snurr, R. Q. Identifying promising metal–organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory. J. Comput. Chem. 2019, 40, 1305, DOI: 10.1002/jcc.25787
  [Crossref], [PubMed], [CAS], Google Scholar
  23
  Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory
  Rosen, Andrew S.; Notestein, Justin M.; Snurr, Randall Q.
  Journal of Computational Chemistry (2019), 40 (12), 1305-1318CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
  Metal-org. frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chem. compn. and topol. Due to their tunable nature, high-throughput computational screening is a particularly appealing method to reduce the time-to-discovery of MOFs with desirable phys. and chem. properties. In this work, a fully automated, high-throughput periodic d. functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof-of-concept, we use the high-throughput workflow to screen MOFs contg. open metal sites (OMSs) from the Computation-Ready, Exptl. MOF database for the oxidative C-H bond activation of methane. The results from the screening process suggest that, despite the strong C-H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXisVWktr0%253D&md5=13c289f2e38b866b0ab5b7687c40a8d1
24. 24
  Lee, K.; Howe, J. D.; Lin, L. C.; Smit, B.; Neaton, J. B. Small-Molecule Adsorption in Open-Site Metal-Organic Frameworks: A Systematic Density Functional Theory Study for Rational Design. Chem. Mater. 2015, 27, 668– 678, DOI: 10.1021/cm502760q
  [ACS Full Text ], [CAS], Google Scholar
  24
  Small-Molecule Adsorption in Open-Site Metal-Organic Frameworks: A Systematic Density Functional Theory Study for Rational Design
  Lee, Kyuho; Howe, Joshua D.; Lin, Li-Chiang; Smit, Berend; Neaton, Jeffrey B.
  Chemistry of Materials (2015), 27 (3), 668-678CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  Using d. functional theory, the authors systematically computed and investigated the binding enthalpies of 14 different small mols. in a series of isostructural metal-org. frameworks, M-MOF-74, with M = Mg, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn. The small mols. considered include major flue-gas components, trace gases, and small hydrocarbons, i.e., H2, CO, CO2, H2O, H2S, N2, NH3, SO2, CH4, C2H2, C2H4, C2H6, C3H6, and C3H8. In total, the adsorption energetics of 140 unique systems are presented and discussed. Dispersion interactions were included by employing a non-local van der Waals d. functional, vdW-DF2. Hubbard U corrections were applied to the localized d electrons of transition metal atoms, and the impact of such corrections was assessed quant. For systems for which measured binding enthalpies have been reported, these calcns. lead to excellent overall agreement with exptl. detd. structures and isosteric heats of adsorption. For systems that have yet to be realized or characterized, this study provides quant. predictions, establishes a better understanding of the role of different transition-metal cations in small-mol. binding at open-metal sites, and identifies routes for predicting potential candidates for energy-related gas-sepn. applications. For example, the authors predict that Cu-MOF-74 will exhibit selectivity of CO2 over H2O and that Mn-MOF-74 can be used to sep. trace flue-gas impurities and toxic gases from gas mixts.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFOku7vM&md5=d07ba6dc8fae92cd042217e73d1ed78d
25. 25
  Odoh, S. O.; Cramer, C. J.; Truhlar, D. G.; Gagliardi, L. Quantum-Chemical Characterization of the Properties and Reactivities of Metal–Organic Frameworks. Chem. Rev. 2015, 115, 6051– 6111, DOI: 10.1021/cr500551h
  [ACS Full Text ], [CAS], Google Scholar
  25
  Quantum-Chemical Characterization of the Properties and Reactivities of Metal-Organic Frameworks
  Odoh, Samuel O.; Cramer, Christopher J.; Truhlar, Donald G.; Gagliardi, Laura
  Chemical Reviews (Washington, DC, United States) (2015), 115 (12), 6051-6111CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. The following topic are discussed: Design and potential uses of MOFs; Electronic structure methods (Hartree-Fock, MP2, CC, CASSCF, DFT including various functionals, TDDFT, periodic DFT and DFT+U, combined Quantum-mech. and Mol.-mech. methods); Properties of MOFs; Gas adsorption and sepn.; Catalysis and reactivity (oxidn., hydrogenation, and Knoevenagel condensation reactions).
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXmsFyis7w%253D&md5=ca28570cc0e94eb3c784747f5b6060df
26. 26
  Frenkel, D.; Smit, B. Understanding Molecular Simulations: from Algorithms to Applications, 2nd ed.; Academic Press: San Diego, 2002.
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
27. 27
  Smit, B.; Maesen, T. L. M. Molecular Simulations of Zeolites: Adsorption, Diffusion, and Shape Selectivity. Chem. Rev. 2008, 108, 4125– 4184, DOI: 10.1021/cr8002642
  [ACS Full Text ], [CAS], Google Scholar
  27
  Molecular Simulations of Zeolites: Adsorption, Diffusion, and Shape Selectivity
  Smit, Berend; Maesen, Theo L. M.
  Chemical Reviews (Washington, DC, United States) (2008), 108 (10), 4125-4184CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. Details of simulation studies for adsorption, diffusion, and shape selectivity on zeolites have been reviewed.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFKlurrL&md5=7a607f8f328c57fb1c88a004d4cf04da
28. 28
  Gropp, C.; Canossa, S.; Wuttke, S.; Gándara, F.; Li, Q.; Gagliardi, L.; Yaghi, O. M. Standard Practices of Reticular Chemistry. ACS Cent. Sci. 2020, 6, 1255, DOI: 10.1021/acscentsci.0c00592
  [ACS Full Text ], [CAS], Google Scholar
  28
  Standard Practices of Reticular Chemistry
  Gropp, Cornelius; Canossa, Stefano; Wuttke, Stefan; Gandara, Felipe; Li, Qiaowei; Gagliardi, Laura; Yaghi, Omar M.
  ACS Central Science (2020), 6 (8), 1255-1273CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
  A review. Since 1995 when the first of metal-org. frameworks was crystd. with the strong bond approach, where metal ions are joined by charged org. linkers exemplified by carboxylates, followed by proof of their porosity in 1998 and ultrahigh porosity in 1999, a revolution in the development of their chem. has ensued. This is being reinforced by the discovery of two- and three-dimensional covalent org. frameworks in 2005 and 2007. Currently, the chem. of such porous, cryst. frameworks is collectively referred to as reticular chem., which is being practiced in over 100 countries. The involvement of researchers from various backgrounds and fields, and the vast scope of this chem. and its societal applications, necessitate articulating the "Std. Practices of Reticular Chem.". Reticular chem. is a growing field of science with a multitude of practitioners with diverse frames of thinking, making the need for std. practices and quality indicators ever more compelling.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlans7%252FI&md5=d5842bd4eab4542bb6a405ffdaa33fc3
29. 29
  The Cambridge Structural Database. ccdc.cam.ac.uk/solutions/csd-system/components/csd (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
30. 30
  Shevchenko, A. P.; Eremin, R. A.; Blatov, V. A. The CSD and knowledge databases: from answers to questions. CrystEngComm 2020, in press. DOI: 10.1039/D0CE00265H
  [Crossref], [PubMed], Google Scholar
  There is no corresponding record for this reference.
31. 31
  Van Heest, T.; Teich-McGoldrick, S. L.; Greathouse, J. A.; Allendorf, M. D.; Sholl, D. S. Identification of metal-organic framework materials for adsorption separation of rare gases: Applicability of ideal adsorbed solution theory (IAST) and effects of inaccessible framework regions. J. Phys. Chem. C 2012, 116, 13183– 13195, DOI: 10.1021/jp302808j
  [ACS Full Text ], [CAS], Google Scholar
  31
  Identification of Metal-Organic Framework Materials for Adsorption Separation of Rare Gases: Applicability of Ideal Adsorbed Solution Theory (IAST) and Effects of Inaccessible Framework Regions
  Van Heest, Timothy; Teich-McGoldrick, Stephanie L.; Greathouse, Jeffery A.; Allendorf, Mark D.; Sholl, David S.
  Journal of Physical Chemistry C (2012), 116 (24), 13183-13195CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
  A collection of >3000 MOFs with exptl. confirmed structures were screened for performance in three binary sepns.: Ar/Kr, Kr/Xe, and Xe/Rn. 70 materials were selected for further anal., and calcns. were performed to account for inaccessible regions. Single component GCMC calcns. were performed to parametrize IAST calcns. on these 70 materials. An approach that avoids possible imprecision in IAST due to curve-fitting of single component isotherms is introduced. The precision of IAST for these gas pairs was confirmed with extensive binary GCMC calcns. For each binary sepn., materials were identified with predicted performance that surpasses the state of the art. A significant no. of materials are reverse selective in the sense that a smaller gas species is preferably adsorbed over a larger species. The phys. origin of this phenomenon is explained. The effect of temp. on sepn. performance was also examd.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XnsVKlurY%253D&md5=57e20f1fe778adb9f3382dc54284ee6e
32. 32
  Watanabe, T.; Sholl, D. S. Accelerating Applications of Metal–Organic Frameworks for Gas Adsorption and Separation by Computational Screening of Materials. Langmuir 2012, 28, 14114– 14128, DOI: 10.1021/la301915s
  [ACS Full Text ], [CAS], Google Scholar
  32
  Accelerating Applications of Metal-Organic Frameworks for Gas Adsorption and Separation by Computational Screening of Materials
  Watanabe, Taku; Sholl, David S.
  Langmuir (2012), 28 (40), 14114-14128CODEN: LANGD5; ISSN:0743-7463. (American Chemical Society)
  The selection of metal-org. frameworks (MOFs) for gas adsorption and sepn. has become a significant challenge over the past decade because of the large no. of new structures reported every year. We applied a multiscale computational approach to screen existing MOFs for CO2/N2 sepn. Pore characteristics of 1163 MOFs were analyzed by the method developed by Haldoupis, Nair, and Sholl (Haldoupis, E.; Nair, S.; Sholl, D. S. J. Am. Chem. Soc.2010, 132, 7528) using a simple steric model. On the basis of the pore size anal., 359 MOFs were examd. by classical mol. simulations. Adsorption and diffusion properties were computed using grand canonical Monte Carlo (GCMC) and mol. dynamics (MD) simulations, resp. These mol. simulations were used to assess which materials hold the greatest promise as membrane materials for CO2/N2 sepns. Finally, d. functional theory (DFT) calcns. were performed to provide preliminary information on the dynamic framework motion of selected MOFs.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVSmurfE&md5=cf6a8db16f92e64ef59a297af92ee0cf
33. 33
  Goldsmith, J.; Wong-Foy, A. G.; Cafarella, M. J.; Siegel, D. J. Theoretical Limits of Hydrogen Storage in Metal–Organic Frameworks: Opportunities and Trade-Offs. Chem. Mater. 2013, 25, 3373– 3382, DOI: 10.1021/cm401978e
  [ACS Full Text ], [CAS], Google Scholar
  33
  Theoretical Limits of Hydrogen Storage in Metal-Organic Frameworks: Opportunities and Trade-Offs
  Goldsmith, Jacob; Wong-Foy, Antek G.; Cafarella, Michael J.; Siegel, Donald J.
  Chemistry of Materials (2013), 25 (16), 3373-3382CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  Because of their high surface areas, crystallinity, and tunable properties, metal-org. frameworks (MOFs) have attracted interest as next-generation materials for gas capture and storage. While much effort was devoted to the discovery of new MOFs, a vast catalog of existing MOFs resides within the Cambridge Structural Database (CSD), many of whose gas uptake properties have not been assessed. Here the authors employ data mining and automated structure anal. to identify, cleanup, and rapidly predict the H storage properties of these compds. Approx. 20,000 candidate compds. were generated from the CSD using an algorithm that removes solvent/guest mols. These compds. were then characterized with respect to their surface area and porosity. Employing the empirical relation between excess H2 uptake and surface area, the authors predict the theor. total H storage capacity for the subset of ∼4000 compds. exhibiting nontrivial internal porosity. The screening identifies several overlooked compds. having high theor. capacities; these compds. are suggested as targets of opportunity for addnl. exptl. characterization. More importantly, screening reveals that the relation between gravimetric and volumetric H2 d. is concave downward, with maximal volumetric performance occurring for surface areas of 3100-4800 m2/g. H2 storage in MOFs will not benefit from further improvements in surface area alone. Rather, discovery efforts should aim to achieve moderate mass densities and surface areas simultaneously, while ensuring framework stability upon solvent removal.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFOqtLjO&md5=b1e813cea5e39d4b1c7760c20ff32f2e
34. 34
  Chung, Y. G.; Camp, J.; Haranczyk, M.; Sikora, B. J.; Bury, W.; Krungleviciute, V.; Yildirim, T.; Farha, O. K.; Sholl, D. S.; Snurr, R. Q. Computation-ready, experimental metal-organic frameworks: a tool to enable high-throughput screening of nanoporous crystals. Chem. Mater. 2014, 26, 6185– 6192, DOI: 10.1021/cm502594j
  [ACS Full Text ], [CAS], Google Scholar
  34
  Computation-Ready, Experimental Metal-Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals
  Chung, Yongchul G.; Camp, Jeffrey; Haranczyk, Maciej; Sikora, Benjamin J.; Bury, Wojciech; Krungleviciute, Vaiva; Yildirim, Taner; Farha, Omar K.; Sholl, David S.; Snurr, Randall Q.
  Chemistry of Materials (2014), 26 (21), 6185-6192CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  Exptl. refined crystal structures for metal-org. frameworks (MOFs) often include solvent mols. and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, the authors have constructed a database of MOF structures that are derived from exptl. data but are immediately suitable for mol. simulations. The computation-ready, exptl. (CoRE) MOF database contains over 4700 porous structures with publically available at. coordinates. Important phys. and chem. properties including the surface area and pore dimensions are reported for these structures. To demonstrate the utility of the database, the authors performed grand canonical Monte Carlo simulations of methane adsorption on all structures in the CoRE MOF database. The authors studied the structural properties of the CoRE MOFs that govern methane storage capacity and found that these relations agree well with those derived recently from a large database of hypothetical MOFs.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Oiur7E&md5=3ad2adec61ab717772baf1380e04cf7a
35. 35
  Nazarian, D.; Camp, J. S.; Sholl, D. S. A Comprehensive Set of High-Quality Point Charges for Simulations of Metal–Organic Frameworks. Chem. Mater. 2016, 28, 785– 793, DOI: 10.1021/acs.chemmater.5b03836
  [ACS Full Text ], [CAS], Google Scholar
  35
  A Comprehensive Set of High-Quality Point Charges for Simulations of Metal-Organic Frameworks
  Nazarian, Dalar; Camp, Jeffrey S.; Sholl, David S.
  Chemistry of Materials (2016), 28 (3), 785-793CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  Most classical simulations of metal-org. frameworks model electrostatic interactions using point charges on each atom in the structure. We report at. point charges derived from periodic d. functional theory (DFT) electronic structure calcns. for more than 2000 unique exptl. synthesized metal-org. frameworks (MOFs). These charges are publicly available as a supplement to the Computation-Ready Exptl. MOF database. These DFT-derived at. point charges are compared to semiempirical group contribution and charge equilibration methods for assigning charges. As an example of using these charges, we examd. each MOF for usefulness in the adsorptive removal of tert-Bu mercaptan (TBM) from natural gas. Monte Carlo simulations revealed many candidate MOF structures with high selectivity for TBM over CH4 and high TBM capacity. We anticipate that this public data set of at. point charges for MOFs will facilitate high-throughput screening for a wide variety of applications in which electrostatic interactions must be considered.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XjvFersw%253D%253D&md5=44bb2616d70ad59ffdd726f4af9dcd3d
36. 36
  Nazarian, D.; Camp, J. S.; Chung, Y. G.; Snurr, R. Q.; Sholl, D. S. Large-scale refinement of metal-organic framework structures using density Functional Theory. Chem. Mater. 2017, 29, 2521– 2528, DOI: 10.1021/acs.chemmater.6b04226
  [ACS Full Text ], [CAS], Google Scholar
  36
  Large-Scale Refinement of Metal-Organic Framework Structures Using Density Functional Theory
  Nazarian, Dalar; Camp, Jeffrey S.; Chung, Yongchul G.; Snurr, Randall Q.; Sholl, David S.
  Chemistry of Materials (2017), 29 (6), 2521-2528CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  Efforts to computationally characterize large nos. of nanoporous materials often rely on databases of exptl. resolved crystal structures. The accuracy of exptl. crystal structures used in such calcns. has a significant impact on the reliability of the results. In this work, we report structures optimized using periodic d. functional theory (DFT) for more than 800 exptl. synthesized metal-org. frameworks (MOFs). Many MOFs changed significantly upon structural optimization, particularly materials that were crystallog. resolved in their solvated form. For each MOF, we simulated the adsorption of CH4 and CO2 using grand canonical Monte Carlo both before and after DFT optimization. The DFT optimization has a large impact on simulated gas adsorption in some cases - for example, CO2 loading at 1 bar changed by more than 25% in over 25% of the MOFs we considered.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVGqsbzE&md5=1e92027e1b8257e1dac60409d975a717
37. 37
  Ongari, D.; Boyd, P. G.; Kadioglu, O.; Mace, A. K.; Keskin, S.; Smit, B. Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials. J. Chem. Theory Comput. 2019, 15, 382– 401, DOI: 10.1021/acs.jctc.8b00669
  [ACS Full Text ], [CAS], Google Scholar
  37
  Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials
  Ongari, Daniele; Boyd, Peter G.; Kadioglu, Ozge; Mace, Amber K.; Keskin, Seda; Smit, Berend
  Journal of Chemical Theory and Computation (2019), 15 (1), 382-401CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  Charge equilibration (Qeq) methods can est. the electrostatic potential of mols. and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute d. functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar mols. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in metal-org. frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality DFT-derived DDEC charges for 2338 MOF structures. We focused on the systematic errors that are attributable to specific atom types to quantify the final precision that one can expect from Qeq methods in the context of gas adsorption where the electrostatic potential plays a significant role, namely, CO2 and H2S adsorption. In conclusion, both the type of algorithm and the input parameters have a large impact on the resulting charges, and we draw some guidelines to help the user to choose the proper combination of the two for obtaining a meaningful set of charges. We show that, considering this set of MOFs, the accuracy of the original Qeq scheme is often still comparable with the most recent variants, even if it clearly fails in the presence of certain atom types, such as alkali metals.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXitFKnu7%252FE&md5=b681aaba638f7f133a157d2df13e7aa9
38. 38
  Qiao, Z.; Zhang, K.; Jiang, J. In silico screening of 4764 computation-ready, experimental metal–organic frameworks for CO 2 separation. J. Mater. Chem. A 2016, 4, 2105– 2114, DOI: 10.1039/C5TA08984K
  [Crossref], [CAS], Google Scholar
  38
  In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation
  Qiao, Zhiwei; Zhang, Kang; Jiang, Jianwen
  Journal of Materials Chemistry A: Materials for Energy and Sustainability (2016), 4 (6), 2105-2114CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
  We report a mol. simulation study to screen 4764 computation-ready, exptl. metal-org. frameworks (CoRE-MOFs) for CO2 sepn. from flue gas (CO2/N2) and natural gas (CO2/CH4). Quant. relationships are established, for the first time, between the metal type and adsorbent evaluation criteria (adsorption selectivity and capacity, working capacity and regenerability). It is found that alkalis exist in 75% of alkali-MOFs as nonframework ions or open metal sites, and 75% of alk.-MOFs contain alkalines as open metal sites; thus alkali- and alk.-MOFs exhibit high adsorption selectivity and large capacity. Combining selectivity, working capacity and regenerability, however, alkali- and alk.-MOFs possess the lowest performance for CO2 sepn. Among ∼1000 lanthanide-based CoRE-MOFs, 50% contain lanthanides as open metal sites and have the highest performance. The best 30 CoRE-MOFs are identified for CO2/N2 and CO2/CH4 sepn., and they mostly contain lanthanides. Furthermore, we predict the breakthrough curves in two identified CoRE-MOFs and demonstrate their superior sepn. performance. This modeling study highlights the central importance of adsorbent evaluation by holistic criteria, and suggests that lanthanides could be interesting metals in the design of new MOFs for CO2 sepn.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVCltbjI&md5=729fc33df7b0e0d675eb68f03a7b9797
39. 39
  Erdös, M.; de Lange, M. F.; Kapteijn, F.; Moultos, O. A.; Vlugt, T. J. H. In Silico Screening of Metal–Organic Frameworks for Adsorption-Driven Heat Pumps and Chillers. ACS Appl. Mater. Interfaces 2018, 10, 27074– 27087, DOI: 10.1021/acsami.8b09343
  [ACS Full Text ], [CAS], Google Scholar
  39
  In Silico Screening of Metal-Organic Frameworks for Adsorption-Driven Heat Pumps and Chillers
  Erdos, Mate; de Lange, Martijn F.; Kapteijn, Freek; Moultos, Othonas A.; Vlugt, Thijs J. H.
  ACS Applied Materials & Interfaces (2018), 10 (32), 27074-27087CODEN: AAMICK; ISSN:1944-8244. (American Chemical Society)
  A computational screening of 2930 exptl. synthesized metal-org. frameworks (MOFs) is carried out to find the best-performing structures for adsorption-driven cooling (AC) applications with methanol and ethanol as working fluids. The screening methodol. consists of four subsequent screening steps for each adsorbate. At the end of each step, the most promising MOFs for AC application are selected for further investigation. In the first step, the structures are selected on the basis of phys. properties (pore limiting diam.). In each following step, points of the adsorption isotherms of the selected structures are calcd. from Monte Carlo simulations in the grand-canonical ensemble. The most promising MOFs are selected on the basis of the working capacity of the structures and the location of the adsorption step (if present), which can be related to the applicable operational conditions in AC. Because of the possibility of reversible pore condensation (first-order phase transition), the mid-d. scheme is used to efficiently and accurately det. the location of the adsorption step. At the end of the screening procedure, six MOFs with high deliverable working capacities (∼0.6 mL working fluid in 1 mL structure) and diverse adsorption step locations are selected for both adsorbates from the original 2930 structures. Because the highest exptl. measured deliverable working capacity to date for MOFs with methanol is ca. 0.45 mL mL-1, the selected six structures show the potential to improve the efficiency of ACs.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlGit77F&md5=632a4d7b307be7d619db2d679daf6ce2
40. 40
  Altintas, C.; Avci, G.; Daglar, H.; Nemati Vesali Azar, A.; Erucar, I.; Velioglu, S.; Keskin, S. An extensive comparative analysis of two MOF databases: high-throughput screening of computation-ready MOFs for CH 4 and H 2 adsorption. J. Mater. Chem. A 2019, 7, 9593– 9608, DOI: 10.1039/C9TA01378D
  [Crossref], [CAS], Google Scholar
  40
  An extensive comparative analysis of two MOF databases: high-throughput screening of computation-ready MOFs for CH4 and H2 adsorption
  Altintas, Cigdem; Avci, Gokay; Daglar, Hilal; Nemati Vesali Azar, Ayda; Erucar, Ilknur; Velioglu, Sadiye; Keskin, Seda
  Journal of Materials Chemistry A: Materials for Energy and Sustainability (2019), 7 (16), 9593-9608CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
  Computation-ready metal-org. framework (MOF) databases (DBs) have tremendous value since they provide directly useable crystal structures for mol. simulations. The currently available two DBs, the CoRE DB (computation-ready, exptl. MOF database) and CSDSS DB (Cambridge Structural Database non-disordered MOF subset) have been widely used in high-throughput mol. simulations. These DBs were constructed using different methods for collecting MOFs, removing bound and unbound solvents, treating charge balancing ions, missing hydrogens and disordered atoms of MOFs. As a result of these methodol. differences, some MOFs were reported under the same name but with different structural features in the two DBs. In this work, we first identified 3490 common MOFs of CoRE and CSDSS DBs and then performed mol. simulations to compute their CH4 and H2 uptakes. We found that 387 MOFs result in different gas uptakes depending on from which DB their structures were taken and we identified them as 'problematic' MOFs. CH4/H2 mixt. adsorption simulations showed that adsorbent performances of problematic MOFs, such as selectivity and regenerability, also significantly change depending on the DB used and lead to large variations in the ranking of materials and identification of the top MOFs. Possible reasons of different structure modifications made by the two DBs were investigated in detail for problematic MOFs. We described five main cases to categorize the problematic MOFs and discussed what types of different modifications were performed by the two DBs in terms of removal of unbound and bound solvents, treatment of missing hydrogen atoms, charge balancing ions etc. with several examples in each case. With this categorization, we aimed to direct researchers to computation-ready MOFs that are the most consistent with their exptl. reported structures. We also provided the new computation-ready structures for 54 MOFs for which the correct structures were missing in both DBs. This extensive comparative anal. of the two DBs will clearly show how and why the DBs differently modified the same MOFs and guide the users to choose either of the computation-ready MOFs from the two DBs depending on their purpose of mol. simulations.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXlslelt70%253D&md5=9d918838e0fd5203b96e6ab969f22b24
41. 41
  Li, A.; Bueno-Perez, R.; Wiggin, S.; Fairen-Jimenez, D. Enabling efficient exploration of metal–organic frameworks in the Cambridge Structural Database. CrystEngComm 2020, in press. DOI: 10.1039/D0CE00299B
  [Crossref], [PubMed], Google Scholar
  There is no corresponding record for this reference.
42. 42
  Barthel, S.; Alexandrov, E. V.; Proserpio, D. M.; Smit, B. Distinguishing Metal–Organic Frameworks. Cryst. Growth Des. 2018, 18, 1738– 1747, DOI: 10.1021/acs.cgd.7b01663
  [ACS Full Text ], [CAS], Google Scholar
  42
  Distinguishing Metal-Organic Frameworks
  Barthel, Senja; Alexandrov, Eugeny V.; Proserpio, Davide M.; Smit, Berend
  Crystal Growth & Design (2018), 18 (3), 1738-1747CODEN: CGDEFU; ISSN:1528-7483. (American Chemical Society)
  We consider two metal-org. frameworks as identical if they share the same bond network respecting the atom types. An algorithm is presented that decides whether two metal-org. frameworks are the same. It is based on distinguishing structures by comparing a set of descriptors that is obtained from the bond network. We demonstrate our algorithm by analyzing the CoRe MOF database of DFT optimized structures with DDEC partial at. charges using the program package ToposPro.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhslyqtrY%253D&md5=ad3b3610b1f238eea55aa9303bd2fa06
43. 43
  Chen, T.; Manz, T. A. Identifying misbonded atoms in the 2019 CoRE metal–organic framework database. RSC Adv. 2020, 10, 26944– 26951, DOI: 10.1039/D0RA02498H
  [Crossref], [CAS], Google Scholar
  43
  Identifying misbonded atoms in the 2019 CoRE metal-organic framework database
  Chen, Taoyi; Manz, Thomas A.
  RSC Advances (2020), 10 (45), 26944-26951CODEN: RSCACL; ISSN:2046-2069. (Royal Society of Chemistry)
  Databases of exptl.-derived metal-org. framework (MOF) crystal structures are useful for large-scale computational screening to identify which MOFs are best-suited for particular applications. However, these crystal structures must be cleaned to identify and/or correct various artifacts. Herein, further cleaning of the 2019 CoRE MOF database is performed to identify structures with misbonded or isolated atoms: (i) structures contg. an isolated atom, (ii) structures contg. atoms too close together (i.e., overlapping atoms), (iii) structures contg. a misplaced hydrogen atom, (iv) structures contg. an under-bonded carbon atom (which might be caused by missing hydrogen atoms), and (v) structures contg. an over-bonded carbon atom. This study should not be viewed as the final cleaning of this database, but rather as progress along the way towards the goal of someday achieving a completely cleaned set of exptl.-derived MOF crystal structures. We performed atom typing for all of the accepted structures to identify those structures that can be parameterized by previously reported forcefield precursors (Chen and Manz, RSC Adv., 2019, 9, 36492-36507). We report several forcefield precursors (e.g., net at. charges, atom-in-material polarizabilities, atom-in-material dispersion coeffs., electron cloud parameters, etc.) for more than five thousand MOFs in the 2019 CoRE MOF database.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhsVSrurrN&md5=5a6580741ead58cdc762224cbda4ecf3
44. 44
  Wilkinson, M. D. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 2016, 3, 160018, DOI: 10.1038/sdata.2016.18
  [Crossref], [PubMed], [CAS], Google Scholar
  44
  The FAIR Guiding Principles for scientific data management and stewardship
  Wilkinson Mark D; Dumontier Michel; Aalbersberg I Jsbrand Jan; Appleton Gabrielle; Dumon Olivier; Groth Paul; Strawn George; Axton Myles; Baak Arie; Blomberg Niklas; Boiten Jan-Willem; da Silva Santos Luiz Bonino; Bourne Philip E; Bouwman Jildau; Brookes Anthony J; Clark Tim; Crosas Merce; Dillo Ingrid; Edmunds Scott; Evelo Chris T; Finkers Richard; Gonzalez-Beltran Alejandra; Rocca-Serra Philippe; Sansone Susanna-Assunta; Gray Alasdair J G; Goble Carole; Grethe Jeffrey S; Heringa Jaap; Kok Ruben; 't Hoen Peter A C; Hooft Rob; Kuhn Tobias; Kok Joost; Lusher Scott J; Mons Barend; Martone Maryann E; Mons Albert; Packer Abel L; Persson Bengt; Roos Marco; Thompson Mark; van Schaik Rene; Schultes Erik; Sengstag Thierry; Slater Ted; Swertz Morris A; van der Lei Johan; van Mulligen Erik; Mons Barend; Velterop Jan; Waagmeester Andra; Wittenburg Peter; Wolstencroft Katherine; Zhao Jun; Mons Barend
  Scientific data (2016), 3 (), 160018 ISSN:.
  There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28bjslyrtQ%253D%253D&md5=e4ce8cf366db2280e54eb0168940720b
45. 45
  Coudert, F. Materials Databases: The Need for Open, Interoperable Databases with Standardized Data and Rich Metadata. Adv. Theory Simulations 2019, 2, 1900131, DOI: 10.1002/adts.201900131
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
46. 46
  Ma, T.; Kapustin, E. A.; Yin, S. X.; Liang, L.; Zhou, Z.; Niu, J.; Li, L.-H.; Wang, Y.; Su, J.; Li, J.; Wang, X.; Wang, W. D.; Wang, W.; Sun, J.; Yaghi, O. M. Single-crystal x-ray diffraction structures of covalent organic frameworks. Science 2018, 361, 48– 52, DOI: 10.1126/science.aat7679
  [Crossref], [PubMed], [CAS], Google Scholar
  46
  Single-crystal x-ray diffraction structures of covalent organic frameworks
  Ma, Tianqiong; Kapustin, Eugene A.; Yin, Shawn X.; Liang, Lin; Zhou, Zhengyang; Niu, Jing; Li, Li-Hua; Wang, Yingying; Su, Jie; Li, Jian; Wang, Xiaoge; Wang, Wei David; Wang, Wei; Sun, Junliang; Yaghi, Omar M.
  Science (Washington, DC, United States) (2018), 361 (6397), 48-52CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
  A review. The crystn. problem is an outstanding challenge in the chem. of porous covalent org. frameworks (COFs). Their structural characterization was limited to modeling and solns. based on powder x-ray or electron diffraction data. Single crystals of COFs amenable to x-ray diffraction characterization were not reported. A general procedure was developed to grow large single crystals of 3-dimensional imine-based COFs (COF-300, hydrated form of COF-300, COF-303, LZU-79, and LZU-111). The high quality of the crystals allowed collection of single-crystal x-ray diffraction data of up to 0.83-Å resoln., leading to unambiguous soln. and precise anisotropic refinement. Characteristics such as degree of interpenetration, arrangement of H2O guests, the reversed imine connectivity, linker disorder, and uncommon topol. were deciphered with at. precision-aspects impossible to det. without single crystals.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1Cjs7zM&md5=9c25f3d95459d93a6affbfb36fef477c
47. 47
  Tong, M.; Lan, Y.; Qin, Z.; Zhong, C. Computation-ready, experimental covalent organic framework for methane delivery: screening and material design. J. Phys. Chem. C 2018, 122, 13009– 13016, DOI: 10.1021/acs.jpcc.8b04742
  [ACS Full Text ], [CAS], Google Scholar
  47
  Computation-Ready, Experimental Covalent Organic Framework for Methane Delivery: Screening and Material Design
  Tong, Minman; Lan, Youshi; Qin, Zhenglong; Zhong, Chongli
  Journal of Physical Chemistry C (2018), 122 (24), 13009-13016CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
  CH4 storage assocd. with adsorbed natural gas technol. attracts considerable researches on finding porous materials with remarkable CH4 delivery performance. In this work, we update the online accessible computation-ready, exptl. (CoRE) covalent org. frameworks (COFs) database with 280 COFs in 12 topologies. All framework structures are constructed and compiled from the resp. exptl. studies and are further evaluated for CH4 delivery. The highest deliverable capacity (DC) between 65 and 5.8 bar among the CoRE COFs is 190 v(STP)/v at 298 K achieved by 3D PI-COF-4. Structure-property relationships show that large volumetric surface area generally benefits CH4 delivery. 2D-COFs can also be top performing materials if constructing their pore channels is passable in three dimensions, as the volumetric surface area will be increased accordingly. This idea can be realized by enlarging the interlayer spacings of 2D-COFs. We also evaluate the DC of CoRE COFs under conditions of 233 K, 65 bar (storage) and 358 K, 5.8 bar (discharge). The highest DC obtained from the CoRE COFs and the designed 2D-COFs are 314 and 337 v(STP)/v, resp.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtVeis7vP&md5=e77a3db672ab59db2e8b1547ed94f4e4
48. 48
  Pizzi, G.; Cepellotti, A.; Sabatini, R.; Marzari, N.; Kozinsky, B. AiiDA: automated interactive infrastructure and database for computational science. Comput. Mater. Sci. 2016, 111, 218– 230, DOI: 10.1016/j.commatsci.2015.09.013
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
49. 49
  Huber, S. P. AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance. Sci. Data 2020, 7, 300, DOI: 10.1038/s41597-020-00638-4
  [Crossref], [PubMed], [CAS], Google Scholar
  49
  AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance
  Huber Sebastiaan P; Zoupanos Spyros; Uhrin Martin; Talirz Leopold; Kahle Leonid; Hauselmann Rico; Yakutovich Aliaksandr V; Andersen Casper W; Ramirez Francisco F; Adorf Carl S; Gargiulo Fernando; Kumbhar Snehal; Passaro Elsa; Johnston Conrad; Cepellotti Andrea; Mounet Nicolas; Marzari Nicola; Pizzi Giovanni; Huber Sebastiaan P; Zoupanos Spyros; Uhrin Martin; Talirz Leopold; Kahle Leonid; Hauselmann Rico; Yakutovich Aliaksandr V; Andersen Casper W; Ramirez Francisco F; Adorf Carl S; Gargiulo Fernando; Kumbhar Snehal; Passaro Elsa; Johnston Conrad; Cepellotti Andrea; Mounet Nicolas; Marzari Nicola; Pizzi Giovanni; Talirz Leopold; Yakutovich Aliaksandr V; Gresch Dominik; Muller Tiziano; Merkys Andrius; Kozinsky Boris; Kozinsky Boris
  Scientific data (2020), 7 (1), 300 ISSN:.
  The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38blvFyksw%253D%253D&md5=89f4a5f6d6a831f029c8cc9f2b2b3246
50. 50
  CURATED covalent organic frameworks database. materialscloud.org/discover/curated-cofs (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
51. 51
  Altundal, O. F.; Altintas, C.; Keskin, S. Can COFs replace MOFs in flue gas separation? high-throughput computational screening of COFs for CO 2 /N 2 separation. J. Mater. Chem. A 2020, 8, 14609, DOI: 10.1039/D0TA04574H
  [Crossref], [CAS], Google Scholar
  51
  Can COFs replace MOFs in flue gas separation? high-throughput computational screening of COFs for CO2/N2 separation
  Altundal, Omer Faruk; Altintas, Cigdem; Keskin, Seda
  Journal of Materials Chemistry A: Materials for Energy and Sustainability (2020), 8 (29), 14609-14623CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
  Covalent org. frameworks (COFs) are under study as adsorbent and membrane candidates for gas sepn. applications. However, exptl. testing of all synthesized COF materials as adsorbents and membranes under different operating conditions is not practical. Herein, the authors used a high-throughput computational screening approach to study adsorption- and membrane-based flue gas sepn. performances of 295 COFs. Adsorption selectivity, working capacity, percent regenerability and adsorbent performance score of COFs were calcd. for sepn. of CO2/N2 mixt. for 3 different cyclic adsorption processes, pressure swing adsorption (PSA), vacuum swing adsorption (VSA) and temp. swing adsorption (TSA). The top performing COFs were identified for each process based on the combination of several metrics. Selectivities of the top COFs were predicted to be greater than those of zeolites and activated carbons. Mol. simulations were performed considering the wet flue gas for the top COF adsorbents and results revealed that most COFs retained their high CO2 selectivities in the presence of H2O. Using COFs with detailed geometry optimization and high-accuracy partial charges in mol. simulations led to lower selectivities and adsorbent performance scores compared to using exptl. reported COFs with approx. charges. Membrane-based flue gas sepn. performances of COFs were also studied and most COFs have comparable CO2 permeabilities with metal org. frameworks (MOFs), up to 3.96 × 106 barrer, however their membrane selectivities were lower than MOFs, 0.38-21, due to their large pores and the lack of metal sites in their frameworks. Structure-performance relations revealed that among the COFs the authors studied, the ones with pore sizes <10 Å, accessible surface areas <4500 m2 g-1 and 0.6 < porosity <0.8 are not only highly selective adsorbents but also CO2 selective membranes.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlynurrM&md5=1322ca870eb69a5b8918f8f26afc3b1f
52. 52
  Lan, Y.; Han, X.; Tong, M.; Huang, H.; Yang, Q.; Liu, D.; Zhao, X.; Zhong, C. Materials genomics methods for high-throughput construction of COFs and targeted synthesis. Nat. Commun. 2018, 9, 1– 10, DOI: 10.1038/s41467-018-07720-x
  [Crossref], [PubMed], [CAS], Google Scholar
  52
  Two high-risk susceptibility loci at 6p25.3 and 14q32.13 for Waldenstrom macroglobulinemia
  McMaster, Mary L.; Berndt, Sonja I.; Zhang, Jianqing; Slager, Susan L.; Li, Shengchao Alfred; Vajdic, Claire M.; Smedby, Karin E.; Yan, Huihuang; Birmann, Brenda M.; Brown, Elizabeth E.; Smith, Alex; Kleinstern, Geffen; Fansler, Mervin M.; Mayr, Christine; Zhu, Bin; Chung, Charles C.; Park, Ju-Hyun; Burdette, Laurie; Hicks, Belynda D.; Hutchinson, Amy; Teras, Lauren R.; Adami, Hans-Olov; Bracci, Paige M.; McKay, James; Monnereau, Alain; Link, Brian K.; Vermeulen, Roel C. H.; Ansell, Stephen M.; Maria, Ann; Diver, W. Ryan; Melbye, Mads; Ojesina, Akinyemi I.; Kraft, Peter; Boffetta, Paolo; Clavel, Jacqueline; Giovannucci, Edward; Besson, Caroline M.; Canzian, Federico; Travis, Ruth C.; Vineis, Paolo; Weiderpass, Elisabete; Montalvan, Rebecca; Wang, Zhaoming; Yeager, Meredith; Becker, Nikolaus; Benavente, Yolanda; Brennan, Paul; Foretova, Lenka; Maynadie, Marc; Nieters, Alexandra; de Sanjose, Silvia; Staines, Anthony; Conde, Lucia; Riby, Jacques; Glimelius, Bengt; Hjalgrim, Henrik; Pradhan, Nisha; Feldman, Andrew L.; Novak, Anne J.; Lawrence, Charles; Bassig, Bryan A.; Lan, Qing; Zheng, Tongzhang; North, Kari E.; Tinker, Lesley F.; Cozen, Wendy; Severson, Richard K.; Hofmann, Jonathan N.; Zhang, Yawei; Jackson, Rebecca D.; Morton, Lindsay M.; Purdue, Mark P.; Chatterjee, Nilanjan; Offit, Kenneth; Cerhan, James R.; Chanock, Stephen J.; Rothman, Nathaniel; Vijai, Joseph; Goldin, Lynn R.; Skibola, Christine F.; Caporaso, Neil E.
  Nature Communications (2018), 9 (1), 1-12CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
  Waldenstrom macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a rare, chronic B-cell lymphoma with high heritability. We conduct a two-stage genome-wide assocn. study of WM/LPL in 530 unrelated cases and 4362 controls of European ancestry and identify two high-risk loci assocd. with WM/LPL at 6p25.3 (rs116446171, near EXOC2 and IRF4; OR = 21.14, 95% CI: 14.40-31.03, P = 1.36 × 10-54) and 14q32.13 (rs117410836, near TCL1; OR = 4.90, 95% CI: 3.45-6.96, P = 8.75 × 10-19). Both risk alleles are obsd. at a low frequency among controls (∼2-3%) and occur in excess in affected cases within families. In silico data suggest that rs116446171 may have functional importance, and in functional studies, we demonstrate increased reporter transcription and proliferation in cells transduced with the 6p25.3 risk allele. Although further studies are needed to fully elucidate underlying biol. mechanisms, together these loci explain 4% of the familial risk and provide insights into genetic susceptibility to this malignancy.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvFGqurbP&md5=34353fe6721d80f7d73498ca40046eb8
53. 53
  Jablonka, K. M.; Ongari, D.; Moosavi, S. M.; Smit, B. Big-Data Science in Porous Materials: Materials Genomics and Machine Learning. Chem. Rev. 2020, 120, 8066, DOI: 10.1021/acs.chemrev.0c00004
  [ACS Full Text ], [CAS], Google Scholar
  53
  Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
  Jablonka, Kevin Maik; Ongari, Daniele; Moosavi, Seyed Mohamad; Smit, Berend
  Chemical Reviews (Washington, DC, United States) (2020), 120 (16), 8066-8129CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. By combining metal nodes with org. linkers we can potentially synthesize millions of possible metal-org. frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too many materials to be processed using conventional, brute force, methods. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We show how to select appropriate training sets, survey approaches that are used to represent these materials in feature space, and review different learning architectures, as well as evaluation and interpretation strategies. In the second part, we review how the different approaches of machine learning have been applied to porous materials. In particular, we discuss applications in the field of gas storage and sepn., the stability of these materials, their electronic properties, and their synthesis. Given the increasing interest of the scientific community in machine learning, we expect this list to rapidly expand in the coming years.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFWjsLnL&md5=e6ec07cd45585938f549be18b31fbf19
54. 54
  Moosavi, S. M.; Nandy, A.; Jablonka, K. M.; Ongari, D.; Janet, J. P.; Boyd, P. G.; Lee, Y.; Smit, B.; Kulik, H. J. Understanding the diversity of the metal-organic framework ecosystem. Nat. Commun. 2020, 11, 4068, DOI: 10.1038/s41467-020-17755-8
  [Crossref], [PubMed], [CAS], Google Scholar
  54
  Understanding the diversity of the metal-organic framework ecosystem
  Moosavi, Seyed Mohamad; Nandy, Aditya; Jablonka, Kevin Maik; Ongari, Daniele; Janet, Jon Paul; Boyd, Peter G.; Lee, Yongjin; Smit, Berend; Kulik, Heather J.
  Nature Communications (2020), 11 (1), 4068CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
  Abstr.: Millions of distinct metal-org. frameworks (MOFs) can be made by combining metal nodes and org. linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new exptl. or predicted structure adds new information. For MOF chemists, the chem. design space is a combination of pore geometry, metal nodes, org. linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chem. design space. In this work, we develop a machine learning method to quantify similarities of MOFs to analyze their chem. diversity. This diversity anal. identifies biases in the databases, and we show that such bias can lead to incorrect conclusions. The developed formalism in this study provides a simple and practical guideline to see whether new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhs1WrsbfE&md5=d9ba7ae4ec44a4716746a8a21b2edf0d
55. 55
  Jablonka, K. M.; Ongari, D.; Smit, B. Applicability of tail corrections in the molecular simulations of porous materials. J. Chem. Theory Comput. 2019, 15, 5635– 5641, DOI: 10.1021/acs.jctc.9b00586
  [ACS Full Text ], [CAS], Google Scholar
  55
  Applicability of Tail Corrections in the Molecular Simulations of Porous Materials
  Jablonka, Kevin Maik; Ongari, Daniele; Smit, Berend
  Journal of Chemical Theory and Computation (2019), 15 (10), 5635-5641CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  Mol. simulations with periodic boundary conditions require the definition of a certain cutoff radius, rc, beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases the use of tail corrections is well-established, which can remedy this truncation of the potential. These corrections are built under the assumption that beyond rc the radial distribution function, g(r), is equal to one. In this work we shed some light on the discussion of whether tail corrections should be used in the modeling of heterogeneous systems. We show that for the adsorption of gases in a diverse set of nanoporous cryst. materials (zeolites, covalent org. frameworks, and metal-org. frameworks), tail corrections are a convenient choice to make the adsorption results less sensitive to the details of the truncation.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1egu7vJ&md5=0894aa136f8cdedb769a0677b84681a3
56. 56
  Yang, Q.; Liu, D.; Zhong, C.; Li, J.-R. Development of Computational Methodologies for Metal–Organic Frameworks and Their Application in Gas Separations. Chem. Rev. 2013, 113, 8261– 8323, DOI: 10.1021/cr400005f
  [ACS Full Text ], [CAS], Google Scholar
  56
  Development of Computational Methodologies for Metal-Organic Frameworks and Their Application in Gas Separations
  Yang, Qingyuan; Liu, Dahuan; Zhong, Chongli; Li, Jian-Rong
  Chemical Reviews (Washington, DC, United States) (2013), 113 (10), 8261-8323CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
  A review. The authors devote the attention to highlighting both the successes and the limitations of various computational methodologies for metal org. frameworks. As an illustration, the authors provide a state of-the-art review on modeling studies of gas sepns. in MOFs using these new methods and concepts. Since the newly developed computational methodologies are normally used in combination with the conventional ones, for the sake of continuity and clarity, some of the conventional methods that have been widely adopted in MOF studies are also briefly discussed.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVKit7bL&md5=0265edb5dc95d324cc20367290c8507c
57. 57
  Hamad, S.; Balestra, S. R.; Bueno-Perez, R.; Calero, S.; Ruiz-Salvador, A. R. Atomic charges for modeling metal-organic frameworks: Why and how. J. Solid State Chem. 2015, 223, 144– 151, DOI: 10.1016/j.jssc.2014.08.004
  [Crossref], [CAS], Google Scholar
  57
  Atomic charges for modeling metal-organic frameworks: Why and how
  Hamad, Said; Balestra, Salvador R. G.; Bueno-Perez, Rocio; Calero, Sofia; Ruiz-Salvador, A. Rabdel
  Journal of Solid State Chemistry (2015), 223 (), 144-151CODEN: JSSCBI; ISSN:0022-4596. (Elsevier B.V.)
  Atomic partial charges are parameters of key importance in the simulation of Metal-Org. Frameworks (MOFs), since Coulombic interactions decrease with the distance more slowly than van der Waals interactions. But despite its relevance, there is no method to unambiguously assign charges to each atom, since at. charges are not quantum observables. There are several methods that allow the calcn. of at. charges, most of them starting from the electronic wavefunction or the electronic d. or the system, as obtained with quantum mechanics calcns. In this work, we describe the most common methods employed to calc. at. charges in MOFs. In order to show the influence that even small variations of structure have on at. charges, we present the results that we obtained for DMOF-1. We also discuss the effect that small variations of at. charges have on the predicted structural properties of IRMOF-1.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVCjtr7K&md5=ac51e68b7f8c6171978011121e75fac2
58. 58
  Mayo, S. L.; Olafson, B. D.; Goddard, W. a. DREIDING: a generic force field for molecular simulations. J. Phys. Chem. 1990, 94, 8897– 8909, DOI: 10.1021/j100389a010
  [ACS Full Text ], [CAS], Google Scholar
  58
  DREIDING: a generic force field for molecular simulations
  Mayo, Stephen L.; Olafson, Barry D.; Goddard, William A., III
  Journal of Physical Chemistry (1990), 94 (26), 8897-909CODEN: JPCHAX; ISSN:0022-3654.
  The parameters are given for a new generic force field, DREIDING, that is useful for predicting structures and dynamics of org., biol., and main-group inorg. mols. The philosophy in DREIDING is to use general force consts. and geometry parameters based on simple hybridization considerations rather than individual force consts. and geometric parameters that depend on the particular combination of atoms involved in the bond, angle, or torsion terms. Thus all bond distances are derived from at. radii, and there is only one force const. each for bonds, angles, and inversions and only six different values for torsional barriers. Parameters are defined for all possible combinations of atoms and new atoms can be added to the force field rather simply. The parameters are given for the "nonmetallic" main-group elements (B, C, N, O, F columns for the C, Si, Ge, and Sn rows) plus H and a few metals (Na, Ca, Zn, Fe). The accuracy of the DREIDING force field is tested by comparing with (i) 76 accurately detd. crystal structures of org. compds. involving H, C, N, O, F, P, S, Cl, and Br, (ii) rotational barriers of a no. of mols., and (iii) relative conformational energies and barriers of a no. of mols. There is excellent agreement.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXmtlyhtL0%253D&md5=c2b2e75dedb934f18bad57d15d8944d4
59. 59
  Rappe, A. K.; Casewit, C. J.; Colwell, K. S.; Goddard, W. a.; Skiff, W. M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 1992, 114, 10024– 10035, DOI: 10.1021/ja00051a040
  [ACS Full Text ], [CAS], Google Scholar
  59
  UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations
  Rappe, A. K.; Casewit, C. J.; Colwell, K. S.; Goddard, W. A., III; Skiff, W. M.
  Journal of the American Chemical Society (1992), 114 (25), 10024-35CODEN: JACSAT; ISSN:0002-7863.
  A new mol. mechanics force field, the Universal force field (UFF), is described wherein the force field parameters are estd. using general rules based only on the element, its hybridization and its connectivity. The force field functional forms, parameters, and generating formulas for the full periodic table are presented.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK38Xmtl2qur8%253D&md5=cf41e8bb9ad299fd5d79f070d690afe1
60. 60
  Potoff, J. J.; Siepmann, J. I. Vapor-liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen. AIChE J. 2001, 47, 1676– 1682, DOI: 10.1002/aic.690470719
  [Crossref], [CAS], Google Scholar
  60
  Vapor-liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen
  Potoff, Jeffrey J.; Siepmann, J. Ilja
  AIChE Journal (2001), 47 (7), 1676-1682CODEN: AICEAC; ISSN:0001-1541. (American Institute of Chemical Engineers)
  New force fields for carbon dioxide and nitrogen are introduced that quant. reproduce the vapor-liq. equil. (VLE) of the neat systems and their mixts. with alkanes. In addn. to the usual VLE calcns. for pure CO2 and N2, calcns. of the binary mixts. with propane were used in the force-field development to achieve a good balance between dispersive and electrostatic (quadrupole-quadrupole) interactions. The transferability of the force fields was then assessed from calcns. of the VLE for the binary mixts. with n-hexane, the binary mixt. of CO2/N2, and the ternary mixt. of CO2/N2/propane. The VLE calcns. were carried out using configurational-bias Monte Carlo simulations in either the grand canonical ensemble with histogram-reweighting or in the Gibbs ensemble.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXlsVCrt78%253D&md5=ad43c62adf3f96989c660eeff73b73e2
61. 61
  Awesome Materials Informatics. github.com/tilde-lab/awesome-materials-informatics (accessed on July 2020).
  Google Scholar
  There is no corresponding record for this reference.
62. 62
  Jain, A.; Ong, S. P.; Chen, W.; Medasani, B.; Qu, X.; Kocher, M.; Brafman, M.; Petretto, G.; Rignanese, G.-M.; Hautier, G.; Gunter, D.; Persson, K. A. FireWorks: a dynamic workflow system designed for high-throughput applications. Concurr. Comput. Pract. Exp. 2015, 27, 5037– 5059, DOI: 10.1002/cpe.3505
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
63. 63
  Curtarolo, S.; Setyawan, W.; Hart, G. L.; Jahnatek, M.; Chepulskii, R. V.; Taylor, R. H.; Wang, S.; Xue, J.; Yang, K.; Levy, O.; Mehl, M. J.; Stokes, H. T.; Demchenko, D. O.; Morgan, D. AFLOW: An automatic framework for high-throughput materials discovery. Comput. Mater. Sci. 2012, 58, 218– 226, DOI: 10.1016/j.commatsci.2012.02.005
  [Crossref], [CAS], Google Scholar
  63
  AFLOW: An automatic framework for high-throughput materials discovery
  Curtarolo, Stefano; Setyawan, Wahyu; Hart, Gus L. W.; Jahnatek, Michal; Chepulskii, Roman V.; Taylor, Richard H.; Wang, Shidong; Xue, Junkai; Yang, Kesong; Levy, Ohad; Mehl, Michael J.; Stokes, Harold T.; Demchenko, Denis O.; Morgan, Dane
  Computational Materials Science (2012), 58 (), 218-226CODEN: CMMSEM; ISSN:0927-0256. (Elsevier B.V.)
  Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compds. and metastable structures, electronic structure, surface, and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present Aflow (Automatic Flow), a software framework for high-throughput calcn. of crystal structure properties of alloys, intermetallics and inorg. compds. The Aflow software is available for the scientific community on the website of the materials research consortium, aflowlib.org. Its geometric and electronic structure anal. and manipulation tools are addnl. available for online operation at the same website. The combination of automatic methods and user online interfaces provide a powerful tool for efficient quantum computational materials discovery and characterization.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktL8%253D&md5=8129bab53c054672274b0d6fa64172ef
64. 64
  Adorf, C. S.; Dodd, P. M.; Ramasubramani, V.; Glotzer, S. C. Simple data and workflow management with the signac framework. Comput. Mater. Sci. 2018, 146, 220– 229, DOI: 10.1016/j.commatsci.2018.01.035
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
65. 65
  Simon, C. M.; Braun, E.; Carraro, C.; Smit, B. Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, E287– E296, DOI: 10.1073/pnas.1613874114
  [Crossref], [PubMed], [CAS], Google Scholar
  65
  Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties
  Simon, Cory M.; Braun, Efrem; Carraro, Carlo; Smit, Berend
  Proceedings of the National Academy of Sciences of the United States of America (2017), 114 (3), E287-E296CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
  Some nanoporous, cryst. materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest mols., which qual. impacts adsorption behavior. The authors pose and solve a statistical mech. model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest mols. incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. The model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and sepns., chem. sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXitlWltQ%253D%253D&md5=e49d7e160f19f212ee4c62b67a1a1099
66. 66
  Haranczyk, M.; Sethian, J. A. Automatic structure analysis in high-throughput characterization of porous materials. J. Chem. Theory Comput. 2010, 6, 3472– 3480, DOI: 10.1021/ct100433z
  [ACS Full Text ], [CAS], Google Scholar
  66
  Automatic Structure Analysis in High-Throughput Characterization of Porous Materials
  Haranczyk, Maciej; Sethian, James A.
  Journal of Chemical Theory and Computation (2010), 6 (11), 3472-3480CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  Inspection of the structure and the void space of a porous material is a crit. step in most computational studies involving guest mols. Some sections of the void space, like inaccessible pockets, have to be identified and blocked in mol. simulations. These pockets are typically detected by visual anal. of the geometry, potential, or free energy landscapes, or a histogram of an initial mol. simulation. Such visual anal. is time-consuming and inhibits characterization of large sets of materials required in studies focused on identification of the best materials for a given application. An automatic approach is presented that bypasses manual visual anal. of this kind, thereby enabling execution of mol. simulations in an unsupervised, high-throughput manner. In the approach, a partial differential equations-based front propagation technique is used to segment out channels and inaccessible pockets of a periodic unit cell of a material. The problem is casted as a path planning problem in 3D space representing a periodic fragment of porous material, and solve the resulting Eikonal equation by using fast marching methods. One attractive feature of this approach is that the to-be-analyzed data can be of varying types, including, for example, a 3D grid representing the distance to the material's surface, the potential or free energy of a mol. inside the material, or even a histogram (a set of snapshots) from a mol. simulation showing areas which were visited by the mol. during the simulation.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht12jurnF&md5=35a2f75a1726480be59e513dd987e445
67. 67
  Fairen-Jimenez, D.; Moggach, S. A.; Wharmby, M. T.; Wright, P. A.; Parsons, S.; Düren, T. Opening the gate: Framework flexibility in ZIF-8 explored by experiments and simulations. J. Am. Chem. Soc. 2011, 133, 8900– 8902, DOI: 10.1021/ja202154j
  [ACS Full Text ], [CAS], Google Scholar
  67
  Opening the Gate: Framework Flexibility in ZIF-8 Explored by Experiments and Simulations
  Fairen-Jimenez, D.; Moggach, S. A.; Wharmby, M. T.; Wright, P. A.; Parsons, S.; Duren, T.
  Journal of the American Chemical Society (2011), 133 (23), 8900-8902CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  ZIF-8 is a zeolitic imidazole-based metal-org. framework with large cavities interconnected by narrow windows. Because the small size of the windows, it allows in principle for mol. sieving of gases such as H2 and CH4. However, the unexpected adsorption of large mols. on ZIF-8 suggests the existence of structural flexibility. ZIF-8 flexibility is explored combining different exptl. techniques with mol. simulation. The ZIF-8 structure is modified by gas adsorption uptake in the same way as it is at a very high pressure (i.e., 14,700 bar) due to a swing effect in the imidazolate linkers, giving access to the porosity. Tuning the flexibility, and so the opening of the small windows, has a further impact on the design of advanced mol. sieving membrane materials for gas sepn., adjusting the access of fluids to the porous network.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmtlWrt70%253D&md5=f9d8904cd7cd4f8d703600d849849f8c
68. 68
  Kolokolov, D. I.; Stepanov, A. G.; Jobic, H. Mobility of the 2-Methylimidazolate Linkers in ZIF-8 Probed by 2H NMR: Saloon Doors for the Guests. J. Phys. Chem. C 2015, 119, 27512– 27520, DOI: 10.1021/acs.jpcc.5b09312
  [ACS Full Text ], [CAS], Google Scholar
  68
  Mobility of the 2-Methylimidazolate Linkers in ZIF-8 Probed by 2H NMR: Saloon Doors for the Guests
  Kolokolov, Daniil I.; Stepanov, Alexander G.; Jobic, Herve
  Journal of Physical Chemistry C (2015), 119 (49), 27512-27520CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
  ZIF-8 is one of the most interesting metal-org. frameworks due to its high stability and unique capabilities for hydrocarbons sepn. Its porous network is formed by large almost spherical cavities interconnected by very narrow windows, ∼3.4 Å, which should be too small even for methane. At the same time the direct exptl. observations show that ZIF-8 cavities are able to host even such large mols. as benzene. This effect is assocd. with the flexibility of the cavity widows, arising from dynamical freedom on the 2-methylimidazole (2-mIM) linkers that form the framework. In this work, by means of 2H NMR we show that the 2-mIM linkers of the ZIF-8 are very mobile and their mobility is sensitive to the presence of benzene guest. In contrast with other known MOFs based on linearly bonded carboxylates, in guest-free ZIF-8 the plane of 2-mIM linker exhibits two-site flips within a sector of 2φf = 34° with very low activation barrier (1.5 kJ mol-1) and high rates (∼1012 s-1). Above 380 K the linkers begin to demonstrate addnl. fast librations with gradually increasing amplitudes γlib comparable with the two-site flips (γlib = ±17° above 560 K). This is direct evidence that the ZIF-8 linkers twist notably, thus increasing the aperture of the windows sufficiently to fit very large mols. Upon benzene loading, the geometry of the obsd. motions remains similar but the potential barrier of the linkers flipping rises up to 9 kJ mol-1.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVOrtrrE&md5=b023e7e91500aec760a217e0a240d553
69. 69
  Mace, A.; Barthel, S.; Smit, B. Automated Multiscale Approach to Predict Self-Diffusion from a Potential Energy Field. J. Chem. Theory Comput. 2019, 15, 2127– 2141, DOI: 10.1021/acs.jctc.8b01255
  [ACS Full Text ], [CAS], Google Scholar
  69
  Automated Multiscale Approach To Predict Self-Diffusion from a Potential Energy Field
  Mace, Amber; Barthel, Senja; Smit, Berend
  Journal of Chemical Theory and Computation (2019), 15 (4), 2127-2141CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  For large-scale screening studies there is a need to est. the diffusion of gas mols. in nanoporous materials more efficiently than (brute force) mol. dynamics. In particular for systems with low diffusion coeffs. mol. dynamics can be prohibitively expensive. An alternative is to compute the hopping rates between adsorption sites using transition state theory. For large-scale screening this requires the automatic detection of the transition states between the adsorption sites along the different diffusion paths. Here an algorithm is presented that analyzes energy grids for the moving particles. It detects the energies at which diffusion paths are formed, together with their directions. This allows for easy identification of nondiffusive systems. For diffusive systems, it partitions the grid coordinates assigned to energy basins and transitions states, permitting a transition state theory based anal. of the diffusion. We test our method on CH4 diffusion in zeolites, using a std. kinetic Monte Carlo simulation based on the output of our grid anal. We find that it is accurate, fast, and rigorous without limitations to the geometries of the diffusion tunnels or transition states.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXjvFCksrs%253D&md5=dc6cf6f5950882d172bf169a46b5e9a7
70. 70
  Kloutse, F. A.; Zacharia, R.; Cossement, D.; Chahine, R. Specific heat capacities of MOF-5, Cu-BTC, Fe-BTC, MOF-177 and MIL-53 (Al) over wide temperature ranges: Measurements and application of empirical group contribution method. Microporous Mesoporous Mater. 2015, 217, 1– 5, DOI: 10.1016/j.micromeso.2015.05.047
  [Crossref], [CAS], Google Scholar
  70
  Specific heat capacities of MOF-5, Cu-BTC, Fe-BTC, MOF-177 and MIL-53 (Al) over wide temperature ranges: Measurements and application of empirical group contribution method
  Kloutse, F. A.; Zacharia, R.; Cossement, D.; Chahine, R.
  Microporous and Mesoporous Materials (2015), 217 (), 1-5CODEN: MIMMFJ; ISSN:1387-1811. (Elsevier B.V.)
  Sp. heat capacities of five MOFs: MOF-5, Cu-BTC, Fe-BTC, MIL-53 (Al) and MOF-177 are reported over wide temp. ranges. For MOF-5, which is the primary candidate material down selected by the Hydrogen Storage Engineering Center of Excellence (HSECoE) for cryo-adsorptive vehicular hydrogen storage, sp. heat capacity in the range 2-300 K is obtained by combining the measurements using a Calvet calorimeter and a direct adiabatic relaxation calorimeter while for remaining MOFs, Cps are measured in the temp. range 80-320 K using the Calvet calorimeter alone. All MOFs exhibit monotonically increasing sp. heat capacities with no visible thermal anomalies implying the absence of any temp.-induced phase transitions in the temp. range considered. A simple ion-based group contribution approach is applied to empirically predict the sp. heat capacities of all MOFs at 323 K.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVeisbrK&md5=bc72b049a3f8c91b0aec309fb7dc2092
71. 71
  Kapil, V.; Wieme, J.; Vandenbrande, S.; Lamaire, A.; Van Speybroeck, V.; Ceriotti, M. Modeling the Structural and Thermal Properties of Loaded Metal–Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations. J. Chem. Theory Comput. 2019, 15, 3237– 3249, DOI: 10.1021/acs.jctc.8b01297
  [ACS Full Text ], [CAS], Google Scholar
  71
  Modeling the Structural and Thermal Properties of Loaded Metal-Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations
  Kapil, Venkat; Wieme, Jelle; Vandenbrande, Steven; Lamaire, Aran; Van Speybroeck, Veronique; Ceriotti, Michele
  Journal of Chemical Theory and Computation (2019), 15 (5), 3237-3249CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  Metal-org. frameworks show both fundamental interest and great promise for applications in adsorption-based technologies, such as the sepn. and storage of gases. The flexibility and complexity of the mol. scaffold pose a considerable challenge to atomistic modeling, esp. when also considering the presence of guest mols. We investigate the role played by quantum and anharmonic fluctuations in the archetypical case of MOF-5, comparing the material at various levels of methane loading. Accurate path integral simulations of such effects are made affordable by the introduction of an accelerated simulation scheme and the use of an optimized force field based on first-principles ref. calcns. We find that the level of statistical treatment that is required for predictive modeling depends significantly on the property of interest. The thermal properties of the lattice are generally well described by a quantum harmonic treatment, with the adsorbate behaving in a classical but strongly anharmonic manner. The heat capacity of the loaded framework - which plays an important role in the characterization of the framework and in detg. its stability to thermal fluctuations during adsorption/desorption cycles - requires, however, a full quantum and anharmonic treatment, either by path integral methods or by a simple but approx. scheme. We also present mol.-level insight into the nanoscopic interactions contributing to the material's properties and suggest design principles to optimize them.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXnvFCgsL4%253D&md5=9e7fc9aa110cd247244ddec9f4a0fe8d
72. 72
  Moosavi, S. M.; Boyd, P. G.; Sarkisov, L.; Smit, B. Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids. ACS Cent. Sci. 2018, 4, 832– 839, DOI: 10.1021/acscentsci.8b00157
  [ACS Full Text ], [CAS], Google Scholar
  72
  Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids
  Moosavi, Seyed Mohamad; Boyd, Peter G.; Sarkisov, Lev; Smit, Berend
  ACS Central Science (2018), 4 (7), 832-839CODEN: ACSCII; ISSN:2374-7951. (American Chemical Society)
  Metal-org. frameworks (MOFs) have emerged as versatile materials for applications ranging from gas sepn. and storage, catalysis, and sensing. The attractive feature of MOFs is that by changing the ligand and/or metal, they can be chem. tuned to perform optimally for a given application. In most, if not all, of these applications one also needs a material that has a sufficient mech. stability, but our understanding of how changes in the chem. structure influence mech. stability is limited. In this work, we rationalize how the mech. properties of MOFs are related to framework bonding topol. and ligand structure. We illustrate that the functional groups on the org. ligands can either enhance the mech. stability through formation of a secondary network of non-bonded interactions or soften the material by destabilizing the bonded network of a MOF. In addn., we show that synergistic effect of the bonding network of the material and the secondary network is required to achieve optimal mech. stability of a MOF. The developed mol. insights in this work can be used for systematic improvement of the mech. stability of the materials by careful selection of the functional groups.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFGntbvK&md5=781d4c266a29f4e5aff7ce762651aad5
73. 73
  Moghadam, P. Z.; Rogge, S. M.; Li, A.; Chow, C.-M.; Wieme, J.; Moharrami, N.; Aragones-Anglada, M.; Conduit, G.; Gomez-Gualdron, D. A.; Van Speybroeck, V.; Fairen-Jimenez, D. Structure-Mechanical Stability Relations of Metal-Organic Frameworks via Machine Learning. Matter 2019, 1, 219– 234, DOI: 10.1016/j.matt.2019.03.002
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
74. 74
  Fumanal, M.; Capano, G.; Barthel, S.; Smit, B.; Tavernelli, I. Energy-based descriptors for photo-catalytically active metal–organic framework discovery. J. Mater. Chem. A 2020, 8, 4473– 4482, DOI: 10.1039/C9TA13506E
  [Crossref], [CAS], Google Scholar
  74
  Energy-based descriptors for photo-catalytically active metal-organic framework discovery
  Fumanal, Maria; Capano, Gloria; Barthel, Senja; Smit, Berend; Tavernelli, Ivano
  Journal of Materials Chemistry A: Materials for Energy and Sustainability (2020), 8 (8), 4473-4482CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
  Metal-org. frameworks (MOFs) consist of metal nodes that are connected by org. linkers. They are thus highly chem. tunable materials given the broad range of potential linkers and nodes that can be chosen for their synthesis. Their tunability has recently sparked interest in the development of new MOF photo-catalysts for energy-related applications such as hydrogen (H2) evolution and CO2 redn. The sheer no. of potentially synthesizable MOFs requires defining descriptors that allow prediction of their performance with this aim. Herein we propose a systematic computational protocol to det. two energy-based descriptors that are directly related to the performance of a MOF as a photocatalyst. These descriptors assess the UV-vis light absorption capability and the band energy alignment with respect to redox processes and/or co-catalyst energy levels. High-throughput screening based on cost-effective computations of these features is envisioned to aid the discovery of new promising photoactive systems.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXjvVKms7Y%253D&md5=4d782bebc3bee43259c67f396788d7b7
75. 75
  Gomez, D. A.; Toda, J.; Sastre, G. Screening of hypothetical metal–organic frameworks for H 2 storage. Phys. Chem. Chem. Phys. 2014, 16, 19001– 19010, DOI: 10.1039/C4CP01848F
  [Crossref], [PubMed], [CAS], Google Scholar
  75
  Screening of hypothetical metal-organic frameworks for H2 storage
  Gomez, Diego A.; Toda, Jordi; Sastre, German
  Physical Chemistry Chemical Physics (2014), 16 (35), 19001-19010CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)
  Computational screening throughout a database contg. ∼138,000 metal-org. frameworks (MOFs) was performed to select candidate structures for H storage. A total of 231 structures (of which 79 contain paddle-wheel units) have been selected that meet the gravimetric and volumetric targets at 100 atm and 77 K. Grand Canonical Monte Carlo simulations have been performed to calc. the isotherms and select structures which meet the targets at 50 atm, and also to check the adsorption in the low pressure regime (1 atm). From this a reduced set of 18 structures was analyzed in more detail, regarding not only gravimetric and volumetric uptake but also pore size distribution and pore vol. A few structures with 3% gravimetric uptake at 1 atm and 77 K perform at the best level found so far.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht1KktLvL&md5=6aae1bca7f853d87c92cfa64248224f7
76. 76
  Colón, Y. J.; Fairen-Jimenez, D.; Wilmer, C. E.; Snurr, R. Q. High-throughput screening of porous crystalline materials for hydrogen storage capacity near room temperature. J. Phys. Chem. C 2014, 118, 5383– 5389, DOI: 10.1021/jp4122326
  [ACS Full Text ], [CAS], Google Scholar
  76
  High-Throughput Screening of Porous Crystalline Materials for Hydrogen Storage Capacity near Room Temperature
  Colon, Yamil J.; Fairen-Jimenez, David; Wilmer, Christopher E.; Snurr, Randall Q.
  Journal of Physical Chemistry C (2014), 118 (10), 5383-5389CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
  The hydrogen storage capabilities of 18 383 porous cryst. structures possessing various degrees of Mg functionalization and diverse phys. properties were assessed through combined grand canonical Monte Carlo (GCMC) and quantum mech. approaches. GCMC simulations were performed for pressures of 2 and 100 bar at a temp. of 243 K. Abs. uptake at 100 bar and deliverable capacity between 100-2 bar were calcd. Maximum abs. and deliverable gravimetric capacities were 9.35 and 9.12 wt.%, resp. Volumetrically, abs. and deliverable capacities were 51 and 30 g/L, resp. The results reveal relations between hydrogen uptake and the phys. properties of the materials. It is shown that the introduction of an optimum amt. of magnesium alkoxide to increase the isosteric heat of adsorption is a promising strategy to improve hydrogen uptake and delivery near ambient temp.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXivFWisbY%253D&md5=7c668b77af1e4382069201bd704f6f53
77. 77
  Bobbitt, N. S.; Chen, J.; Snurr, R. Q. High-Throughput Screening of Metal-Organic Frameworks for Hydrogen Storage at Cryogenic Temperature. J. Phys. Chem. C 2016, 120, 27328– 27341, DOI: 10.1021/acs.jpcc.6b08729
  [ACS Full Text ], [CAS], Google Scholar
  77
  High-Throughput Screening of Metal-Organic Frameworks for Hydrogen Storage at Cryogenic Temperature
  Bobbitt, N. Scott; Chen, Jiayi; Snurr, Randall Q.
  Journal of Physical Chemistry C (2016), 120 (48), 27328-27341CODEN: JPCCCK; ISSN:1932-7447. (American Chemical Society)
  Metal-org. frameworks (MOFs) have attracted significant interest as a class of adsorbent materials for gas storage applications, including hydrogen storage for fuel cell vehicles. Here, we evaluated 137 953 hypothetical MOFs for hydrogen storage at cryogenic conditions (77 K) by detg. the deliverable storage capacity between 100 and 2 bar, using grand canonical Monte Carlo simulations. The highest predicted volumetric capacity for a structure in this study is 50 g/L, and the highest gravimetric capacity is almost 25 wt %. We find that the optimal void fraction is 0.9 and the optimal pore diam. is 12-15 Å. MOFs with larger pores have significant regions in the center of the pore with low hydrogen d., which lowers the storage efficiency. We give examples of MOFs with very large pores in which the hydrogen capacity can potentially be increased using catenation or functional groups to reduce the pore size and increase the surface area per vol. We also introduce a screening parameter, the binding fraction, which is the fraction of the unit cell vol. within a given distance of the framework. This metric is inexpensive to compute and is a strong predictor of hydrogen storage capacity. This simple parameter could be used to quickly screen even larger nos. of MOFs for gas adsorption capacity to identify the most promising candidates for more detailed study.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVaktr7N&md5=fd7b7f4d260d528da4c1044bcdd3c6ed
78. 78
  Thornton, A. W.; Simon, C. M.; Kim, J.; Kwon, O.; Deeg, K. S.; Konstas, K.; Pas, S. J.; Hill, M. R.; Winkler, D. A.; Haranczyk, M.; Smit, B. Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage. Chem. Mater. 2017, 29, 2844– 2854, DOI: 10.1021/acs.chemmater.6b04933
  [ACS Full Text ], [CAS], Google Scholar
  78
  Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage
  Thornton, Aaron W.; Simon, Cory M.; Kim, Jihan; Kwon, Ohmin; Deeg, Kathryn S.; Konstas, Kristina; Pas, Steven J.; Hill, Matthew R.; Winkler, David A.; Haranczyk, Maciej; Smit, Berend
  Chemistry of Materials (2017), 29 (7), 2844-2854CODEN: CMATEX; ISSN:0897-4756. (American Chemical Society)
  The Materials Genome is in action: the mol. codes for millions of materials have been sequenced, predictive models have been developed, and now the challenge of hydrogen storage is targeted. Renewably generated hydrogen is an attractive transportation fuel with zero carbon emissions, but its storage remains a significant challenge. Nanoporous adsorbents have shown promising phys. adsorption of hydrogen approaching targeted capacities, but the scope of studies has remained limited. Here the Nanoporous Materials Genome, contg. over 850,000 materials, is analyzed with a variety of computational tools to explore the limits of hydrogen storage. Optimal features that maximize net capacity at room temp. include pore sizes of around 6 Å and void fractions of 0.1, while at cryogenic temps. pore sizes of 10 Å and void fractions of 0.5 are optimal. Our top candidates are found to be com. attractive as "cryo-adsorbents", with promising storage capacities at 77 K and 100 bar with 30% enhancement to 40 g/L, a promising alternative to liquefaction at 20 K and compression at 700 bar.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXjvVWhsr8%253D&md5=1f248dfa32a7542c24626d2f0990b241
79. 79
  Ahmed, A.; Seth, S.; Purewal, J.; Wong-Foy, A. G.; Veenstra, M.; Matzger, A. J.; Siegel, D. J. Exceptional hydrogen storage achieved by screening nearly half a million metal-organic frameworks. Nat. Commun. 2019, 10, 1568, DOI: 10.1038/s41467-019-09365-w
  [Crossref], [PubMed], [CAS], Google Scholar
  79
  Exceptional hydrogen storage achieved by screening nearly half a million metal-organic frameworks
  Ahmed Alauddin; Siegel Donald J; Seth Saona; Wong-Foy Antek G; Matzger Adam J; Purewal Justin; Veenstra Mike; Siegel Donald J; Siegel Donald J; Siegel Donald J
  Nature communications (2019), 10 (1), 1568 ISSN:.
  Few hydrogen adsorbents balance high usable volumetric and gravimetric capacities. Although metal-organic frameworks (MOFs) have recently demonstrated progress in closing this gap, the large number of MOFs has hindered the identification of optimal materials. Here, a systematic assessment of published databases of real and hypothetical MOFs is presented. Nearly 500,000 compounds were screened computationally, and the most promising were assessed experimentally. Three MOFs with capacities surpassing that of IRMOF-20, the record-holder for balanced hydrogen capacity, are demonstrated: SNU-70, UMCM-9, and PCN-610/NU-100. Analysis of trends reveals the existence of a volumetric ceiling at ∼40 g H2 L(-1). Surpassing this ceiling is proposed as a new capacity target for hydrogen adsorbents. Counter to earlier studies of total hydrogen uptake in MOFs, usable capacities in the highest-capacity materials are negatively correlated with density and volumetric surface area. Instead, capacity is maximized by increasing gravimetric surface area and porosity. This suggests that property/performance trends for total capacities may not translate to usable capacities.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M%252Fit1Ghsw%253D%253D&md5=26b8edf94cf43ba2819eb98f1bf873f6
80. 80
  Yazaydın, A. O.; Snurr, R. Q.; Park, T.-H.; Koh, K.; Liu, J.; LeVan, M. D.; Benin, A. I.; Jakubczak, P.; Lanuza, M.; Galloway, D. B.; Low, J. J.; Willis, R. R. Screening of Metal-Organic Frameworks for Carbon Dioxide Capture from Flue Gas Using a Combined Experimental and Modeling Approach. J. Am. Chem. Soc. 2009, 131, 18198– 18199, DOI: 10.1021/ja9057234
  [ACS Full Text ], [CAS], Google Scholar
  80
  Screening of Metal-Organic Frameworks for Carbon Dioxide Capture from Flue Gas Using a Combined Experimental and Modeling Approach
  Yazaydin, A. Ozgur; Snurr, Randall Q.; Park, Tae-Hong; Koh, Kyoungmoo; Liu, Jian; LeVan, M. Douglas; Benin, Annabelle I.; Jakubczak, Paulina; Lanuza, Mary; Galloway, Douglas B.; Low, John J.; Willis, Richard R.
  Journal of the American Chemical Society (2009), 131 (51), 18198-18199CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  A diverse collection of 14 metal-org. frameworks (MOF) for flue gas CO2 capture are reported. Synthesis, characterization, and adsorption measurements for about half the MOF are reported; adsorption data were collected from the literature for the remaining MOF. The diversity of the selected materials will help improve the understanding fo MOF CO2 capture. Also, these data were used to validate a general strategy for mol. modeling of CO2 and other small mols. in MOF. This strategy is fully predicting with no parameter-fitting. This approach can be used to rapidly screen addnl. MOF, saving large amts. of exptl. time and costs. Grand canonical Monte Carlo simulations were performed for a model which included electrostatic and Lennard-Jones interactions among atoms in the system. The framework and individual CO2 mols. are considered to be rigid. Interactions among CO2 mols. were modeled with the TraAPPE force field (J.J. Potoff and J.I. Siepmann, 2001); Lennard-Jones parameters for MOF atoms were taken from DREIDING (S.L. Mayo, et al., 1990) and UFF (A.K. Rappe, et al., 1992) force fields. Partial charges on MOF atoms were derived from d. functional theory calcns.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFShsr7L&md5=ee067ec4cee9d1095897b19d957671db
81. 81
  Haldoupis, E.; Nair, S.; Sholl, D. S. Finding MOFs for highly selective CO 2/N 2 adsorption using materials screening based on efficient assignment of atomic point charges. J. Am. Chem. Soc. 2012, 134, 4313– 4323, DOI: 10.1021/ja2108239
  [ACS Full Text ], [CAS], Google Scholar
  81
  Finding MOFs for Highly Selective CO2/N2 Adsorption Using Materials Screening Based on Efficient Assignment of Atomic Point Charges
  Haldoupis, Emmanuel; Nair, Sankar; Sholl, David S.
  Journal of the American Chemical Society (2012), 134 (9), 4313-4323CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  Electrostatic interactions are a crit. factor in the adsorption of quadrupolar species such as CO2 and N2 in metal-org. frameworks (MOFs) and other nanoporous materials. A version of the semiempirical charge equilibration method suitable for periodic materials can be used to efficiently assign charges and allow mol. simulations for a large no. of MOFs. This approach is illustrated by simulating CO2 and N2 adsorption in ∼500 MOFs; this is the largest set of structures for which this information was reported to date. For materials predicted by the calcns. to have promising adsorption selectivities, the authors performed more detailed calcns. in which accurate quantum chem. methods were used to assign at. point charges, and mol. simulations were used to assess mol. diffusivities and binary adsorption isotherms. The results identify two MOFs, exptl. known to be stable upon solvent removal, that are predicted to show no diffusion limitations for adsorbed mols. and extremely high CO2/N2 adsorption selectivities for CO2 adsorption from dry air and from gas mixts. typical of dry flue gas.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XitF2msb8%253D&md5=3d7fcc3d3e6b5aa43811c380337c0f07
82. 82
  Lin, L.-C.; Berger, A. H.; Martin, R. L.; Kim, J.; Swisher, J. a.; Jariwala, K.; Rycroft, C. H.; Bhown, A. S.; Deem, M. W.; Haranczyk, M.; Smit, B. In silico screening of carbon-capture materials. Nat. Mater. 2012, 11, 633– 641, DOI: 10.1038/nmat3336
  [Crossref], [PubMed], [CAS], Google Scholar
  82
  In silico screening of carbon-capture materials
  Lin, Li-Chiang; Berger, Adam H.; Martin, Richard L.; Kim, Jihan; Swisher, Joseph A.; Jariwala, Kuldeep; Rycroft, Chris H.; Bhown, Abhoyjit S.; Deem, Michael W.; Haranczyk, Maciej; Smit, Berend
  Nature Materials (2012), 11 (7), 633-641CODEN: NMAACR; ISSN:1476-1122. (Nature Publishing Group)
  One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to sep. the CO2 from flue gas. For example, near-term CCS technol. applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. The authors developed a computational approach to rank adsorbents for their performance in CCS. Using this anal., hundreds of thousands of zeolite and zeolitic imidazolate framework structures were screened and many different structures identified that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XnsFKgs7o%253D&md5=492bbeb4268dbad4726e14b2df4a38bf
83. 83
  Qiao, Z.; Zhang, K.; Jiang, J. In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation. J. Mater. Chem. A 2016, 4, 2105– 2114, DOI: 10.1039/C5TA08984K
  [Crossref], [CAS], Google Scholar
  83
  In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation
  Qiao, Zhiwei; Zhang, Kang; Jiang, Jianwen
  Journal of Materials Chemistry A: Materials for Energy and Sustainability (2016), 4 (6), 2105-2114CODEN: JMCAET; ISSN:2050-7496. (Royal Society of Chemistry)
  We report a mol. simulation study to screen 4764 computation-ready, exptl. metal-org. frameworks (CoRE-MOFs) for CO2 sepn. from flue gas (CO2/N2) and natural gas (CO2/CH4). Quant. relationships are established, for the first time, between the metal type and adsorbent evaluation criteria (adsorption selectivity and capacity, working capacity and regenerability). It is found that alkalis exist in 75% of alkali-MOFs as nonframework ions or open metal sites, and 75% of alk.-MOFs contain alkalines as open metal sites; thus alkali- and alk.-MOFs exhibit high adsorption selectivity and large capacity. Combining selectivity, working capacity and regenerability, however, alkali- and alk.-MOFs possess the lowest performance for CO2 sepn. Among ∼1000 lanthanide-based CoRE-MOFs, 50% contain lanthanides as open metal sites and have the highest performance. The best 30 CoRE-MOFs are identified for CO2/N2 and CO2/CH4 sepn., and they mostly contain lanthanides. Furthermore, we predict the breakthrough curves in two identified CoRE-MOFs and demonstrate their superior sepn. performance. This modeling study highlights the central importance of adsorbent evaluation by holistic criteria, and suggests that lanthanides could be interesting metals in the design of new MOFs for CO2 sepn.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVCltbjI&md5=729fc33df7b0e0d675eb68f03a7b9797
84. 84
  Wilmer, C. E.; Leaf, M.; Lee, C. Y.; Farha, O. K.; Hauser, B. G.; Hupp, J. T.; Snurr, R. Q. Large-scale screening of hypothetical metal-organic frameworks. Nat. Chem. 2012, 4, 83– 89, DOI: 10.1038/nchem.1192
  [Crossref], [CAS], Google Scholar
  84
  Large-scale screening of hypothetical metal-organic frameworks
  Wilmer, Christopher E.; Leaf, Michael; Lee, Chang Yeon; Farha, Omar K.; Hauser, Brad G.; Hupp, Joseph T.; Snurr, Randall Q.
  Nature Chemistry (2012), 4 (2), 83-89CODEN: NCAHBB; ISSN:1755-4330. (Nature Publishing Group)
  Metal-org. frameworks (MOFs) are porous materials constructed from modular mol. building blocks, typically metal clusters and org. linkers. These can, in principle, be assembled to form an almost unlimited no. of MOFs, yet materials reported to date represent only a tiny fraction of the possible combinations. Here, the authors demonstrate a computational approach to generate all conceivable MOFs from a given chem. library of building blocks (based on the structures of known MOFs) and rapidly screen them to find the best candidates for a specific application. From a library of 102 building blocks the authors generated 137,953 hypothetical MOFs and for each calcd. the pore-size distribution, surface area and methane-storage capacity. The authors identified over 300 MOFs with a predicted methane-storage capacity better than that of any known material, and this approach also revealed structure-property relations. Methyl-functionalized MOFs were frequently top performers, so the authors selected one such promising MOF and exptl. confirmed its predicted capacity.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVagtL3K&md5=3becbfed2fdacdb8b58146666da7c038
85. 85
  Simon, C. M.; Kim, J.; Gomez-Gualdron, D. a.; Camp, J. S.; Chung, Y. G.; Martin, R. L.; Mercado, R.; Deem, M. W.; Gunter, D.; Haranczyk, M.; Sholl, D. S.; Snurr, R. Q.; Smit, B. The materials genome in action: identifying the performance limits for methane storage. Energy Environ. Sci. 2015, 8, 1190– 1199, DOI: 10.1039/C4EE03515A
  [Crossref], [CAS], Google Scholar
  85
  The materials genome in action: identifying the performance limits for methane storage
  Simon, Cory M.; Kim, Jihan; Gomez-Gualdron, Diego A.; Camp, Jeffrey S.; Chung, Yongchul G.; Martin, Richard L.; Mercado, Rocio; Deem, Michael W.; Gunter, Dan; Haranczyk, Maciej; Sholl, David S.; Snurr, Randall Q.; Smit, Berend
  Energy & Environmental Science (2015), 8 (4), 1190-1199CODEN: EESNBY; ISSN:1754-5706. (Royal Society of Chemistry)
  Analogous to the way the Human Genome Project advanced an array of biol. sciences by mapping the human genome, the Materials Genome Initiative aims to enhance our understanding of the fundamentals of materials science by providing the information we need to accelerate the development of new materials. This approach is particularly applicable to recently developed classes of nanoporous materials, such as metal-org. frameworks (MOFs), which are synthesized from a limited set of mol. building blocks that can be combined to generate a very large no. of different structures. In this Perspective, we illustrate how a materials genome approach can be used to search for high-performance adsorbent materials to store natural gas in a vehicular fuel tank. Drawing upon recent reports of large databases of existing and predicted nanoporous materials generated in silico, we have collected and compared on a consistent basis the methane uptake in over 650 000 materials based on the results of mol. simulation. The data that we have collected provide candidate structures for synthesis, reveal relationships between structural characteristics and performance, and suggest that it may be difficult to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXotVOguw%253D%253D&md5=cb589b6b987ef80816a74c377774980c
86. 86
  Huck, J. M.; Lin, L.-C.; Berger, A. H.; Shahrak, M. N.; Martin, R. L.; Bhown, A. S.; Haranczyk, M.; Reuter, K.; Smit, B. Evaluating different classes of porous materials for carbon capture. Energy Environ. Sci. 2014, 7, 4132– 4146, DOI: 10.1039/C4EE02636E
  [Crossref], [CAS], Google Scholar
  86
  Evaluating different classes of porous materials for carbon capture
  Huck, Johanna M.; Lin, Li-Chiang; Berger, Adam H.; Shahrak, Mahdi Niknam; Martin, Richard L.; Bhown, Abhoyjit S.; Haranczyk, Maciej; Reuter, Karsten; Smit, Berend
  Energy & Environmental Science (2014), 7 (12), 4132-4146CODEN: EESNBY; ISSN:1754-5706. (Royal Society of Chemistry)
  Carbon Capture and Sequestration (CCS) is one of the promising ways to significantly reduce the CO2 emission from power plants. In particular, amongst several sepn. strategies, adsorption by nano-porous materials is regarded as a potential means to efficiently capture CO2 at the place of its origin in a post-combustion process. The search for promising materials in such a process not only requires the screening of a multitude of materials but also the development of an adequate evaluation metric. Several evaluation criteria have been introduced in the literature concg. on a single adsorption or material property at a time. Parasitic energy is a new approach for material evaluation to address the energy load imposed on a power plant while applying CCS. In this work, we evaluate over 60 different materials with respect to their parasitic energy, including exptl. realized and hypothetical materials such as metal-org. frameworks (MOFs), zeolitic imidazolate frameworks (ZIFs), porous polymer networks (PPNs), and zeolites. The results are compared to other proposed evaluation criteria and performance differences are studied regarding the regeneration modes, (i.e.Pressure-Swing (PSA) and Temp.-Swing Adsorption (TSA)) as well as the flue gas compn.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhslGgurbO&md5=f191b21536f25b460c1867f13076745b
87. 87
  Burns, T. D.; Pai, K. N.; Subraveti, S. G.; Collins, S. P.; Krykunov, M.; Rajendran, A.; Woo, T. K. Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Postcombustion CO 2 Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models. Environ. Sci. Technol. 2020, 54, 4536, DOI: 10.1021/acs.est.9b07407
  [ACS Full Text ], [CAS], Google Scholar
  87
  Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Post-combustion CO2 Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models
  Burns, Thomas D.; Pai, Kasturi Nagesh; Subraveti, Sai Gokul; Collins, Sean P.; Krykunov, Mykhaylo; Rajendran, Arvind; Woo, Tom K.
  Environmental Science & Technology (2020), 54 (7), 4536-4544CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
  Post-combustion CO2 capture and storage (CCS) is a key technol. approach to reduce greenhouse gas emissions while humans transition to C-free energy prodn.; however, current solvent-based CO2 capture processes are considered too energetically expensive for widespread deployment. Vacuum swing adsorption (VSA) is a low-energy CCS with the potential for industrial implementation if the right sorbents can be found. Metal-org. framework (MOF) materials are often promoted as sorbents for low-energy CCS by highlighting select adsorption properties without a clear understanding of how they perform in actual VSA processes. Atomistic simulations were fully integrated with a detailed VSA simulator and validated on a pilot scale to screen 1632 exptl. characterized MOF. A total of 482 materials were obsd. to meet the 95% CO2 purity and 90% CO2 recovery targets (95/90-PRT), 365 of which have parasitic energies below that of solvent-based capture (∼290 kWhe/MT CO2) with a low value of 217 kWhe/MT CO2. Machine learning models were developed using common adsorption metrics to predict a material ability to meet the 95/90-PRT with an overall 91% prediction accuracy. Accurate parasitic energy and productivity ests. of a VSA process require full process simulations.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXjs1Wisbo%253D&md5=7fa2c34868cac38202973c1cb71d6793
88. 88
  Farmahini, A. H.; Krishnamurthy, S.; Friedrich, D.; Brandani, S.; Sarkisov, L. From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes. Ind. Eng. Chem. Res. 2018, 57, 15491– 15511, DOI: 10.1021/acs.iecr.8b03065
  [ACS Full Text ], [CAS], Google Scholar
  88
  From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes
  Farmahini, Amir H.; Krishnamurthy, Shreenath; Friedrich, Daniel; Brandani, Stefano; Sarkisov, Lev
  Industrial & Engineering Chemistry Research (2018), 57 (45), 15491-15511CODEN: IECRED; ISSN:0888-5885. (American Chemical Society)
  Multiscale material screening strategies combine mol. simulations and process modeling to identify the best performing adsorbents for a particular application, such as carbon capture. The idea to go from the properties of a single crystal to the prediction of material performance in a real process is both powerful and appealing; however, it is yet to be established how to implement it consistently. In this article, we focus on the challenges assocd. with the interface between mol. and process levels of description. We explore how predictions of the material performance in the actual process depend on the accuracy of mol. simulations, on the procedures to feed the equil. adsorption data into the process simulator, and on the structural characteristics of the pellets, which are not available from mol. simulations and should be treated as optimization parameters. The presented anal. paves the way for more consistent and robust multiscale material screening strategies.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhvVKltL3J&md5=d9f237b44447928b5db6d4eea3df209f
89. 89
  Farmahini, H.; Friedrich, A.; Brandani, D.; Sarkisov, S.; Exploring, L. new sources of efficiency in process-driven materials screening for post-combustion carbon capture. Energy Environ. Sci. 2020, 13, 1018– 1037, DOI: 10.1039/C9EE03977E
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
90. 90
  AiiDA-LSMO plugin. github.com/lsmo-epfl/aiida-lsmo (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
91. 91
  Open Science Means Open Source—Or, at Least, It Should. linuxjournal.com/content/open-science-means-open-source-or-least-it-should (accessed on July 2020).
  Google Scholar
  There is no corresponding record for this reference.
92. 92
  Codes—NOMAD CoE. www.nomad-coe.eu/index.php?page=codes (accessed on July 2020).
  Google Scholar
  There is no corresponding record for this reference.
93. 93
  Ghiringhelli, L. M.; Carbogno, C.; Levchenko, S.; Mohamed, F.; Huhs, G.; Lüders, M.; Oliveira, M.; Scheffler, M. Towards efficient data exchange and sharing for big-data driven materials science: Metadata and data formats. npj Comput. Mater. 2017, 3, 1– 9, DOI: 10.1038/s41524-017-0048-5
  [Crossref], [CAS], Google Scholar
  93
  Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats
  Ghiringhelli, Luca M.; Carbogno, Christian; Levchenko, Sergey; Mohamed, Fawzi; Huhs, Georg; Lueders, Martin; Oliveira, Micael; Scheffler, Matthias
  npj Computational Materials (2017), 3 (1), 1-9CODEN: NCMPCS; ISSN:2057-3960. (Nature Research)
  With big-data driven materials research, the new paradigm of materials science, sharing and wide accessibility of data are becoming crucial aspects. Obviously, a prerequisite for data exchange and big-data analytics is standardization, which means using consistent and unique conventions for, e.g., units, zero base lines, and file formats. There are two main strategies to achieve this goal. One accepts the heterogeneous nature of the community, which comprises scientists from physics, chem., bio-physics, and materials science, by complying with the diverse ecosystem of computer codes and thus develops "converters" for the input and output files of all important codes. These converters then translate the data of each code into a standardized, code-independent format. The other strategy is to provide standardized open libraries that code developers can adopt for shaping their inputs, outputs, and restart files, directly into the same code-independent format. In this perspective paper, we present both strategies and argue that they can and should be regarded as complementary, if not even synergetic. The represented appropriate format and conventions were agreed upon by two teams, the Electronic Structure Library (ESL) of the European Center for Atomic and Mol. Computations (CECAM) and the NOvel MAterials Discovery (NOMAD) Lab., a European Center of Excellence (CoE). A key element of this work is the definition of hierarchical metadata describing state-of-the-art electronic-structure calcns.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1CjsL7L&md5=d24d2dbaf0f5bf0780228166cc56cd14
94. 94
  Clark, S. J.; Segall, M. D.; Pickard, C. J.; Hasnip, P. J.; Probert, M. I. J.; Refson, K.; Payne, M. C. First principles methods using CASTEP. Z. Kristallogr. - Cryst. Mater. 2005, 220, 567– 570, DOI: 10.1524/zkri.220.5.567.65075
  [Crossref], [CAS], Google Scholar
  94
  First principles methods using CASTEP
  Clark, Stewart J.; Segall, Matthew D.; Pickard, Chris J.; Hasnip, Phil J.; Probert, Matt I. J.; Refson, Keith; Payne, Mike C.
  Zeitschrift fuer Kristallographie (2005), 220 (5-6), 567-570CODEN: ZEKRDZ; ISSN:0044-2968. (Oldenbourg Wissenschaftsverlag GmbH)
  The CASTEP code for first principles electronic structure calcns. is described. A brief, non-tech. overview is given and some of the features and capabilities highlighted. Some features which are unique to CASTEP are described and near-future development plans outlined.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXmsVSitbk%253D&md5=edb75e2f9d4df4ad83f4df7db21888e7
95. 95
  CASTEP website. www.castep.org/CASTEP/GettingCASTEP (accessed on June 2020).
  Google Scholar
  There is no corresponding record for this reference.
96. 96
  Fdez. Galván, I. OpenMolcas: From Source Code to Insight. J. Chem. Theory Comput. 2019, 15, 5925– 5964, DOI: 10.1021/acs.jctc.9b00532
  [ACS Full Text ], [CAS], Google Scholar
  96
  OpenMolcas: From Source Code to Insight
  Fdez. Galvan, Ignacio; Vacher, Morgane; Alavi, Ali; Angeli, Celestino; Aquilante, Francesco; Autschbach, Jochen; Bao, Jie J.; Bokarev, Sergey I.; Bogdanov, Nikolay A.; Carlson, Rebecca K.; Chibotaru, Liviu F.; Creutzberg, Joel; Dattani, Nike; Delcey, Mickael G.; Dong, Sijia S.; Dreuw, Andreas; Freitag, Leon; Frutos, Luis Manuel; Gagliardi, Laura; Gendron, Frederic; Giussani, Angelo; Gonzalez, Leticia; Grell, Gilbert; Guo, Meiyuan; Hoyer, Chad E.; Johansson, Marcus; Keller, Sebastian; Knecht, Stefan; Kovacevic, Goran; Kaellman, Erik; Li Manni, Giovanni; Lundberg, Marcus; Ma, Yingjin; Mai, Sebastian; Malhado, Joao Pedro; Malmqvist, Per Aake; Marquetand, Philipp; Mewes, Stefanie A.; Norell, Jesper; Olivucci, Massimo; Oppel, Markus; Phung, Quan Manh; Pierloot, Kristine; Plasser, Felix; Reiher, Markus; Sand, Andrew M.; Schapiro, Igor; Sharma, Prachi; Stein, Christopher J.; Soerensen, Lasse Kragh; Truhlar, Donald G.; Ugandi, Mihkel; Ungur, Liviu; Valentini, Alessio; Vancoillie, Steven; Veryazov, Valera; Weser, Oskar; Wesolowski, Tomasz A.; Widmark, Per-Olof; Wouters, Sebastian; Zech, Alexander; Zobel, J. Patrick; Lindh, Roland
  Journal of Chemical Theory and Computation (2019), 15 (11), 5925-5964CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  In this Article we describe the OpenMolcas environment and invite the computational chem. community to collaborate. The open-source project already includes a large no. of new developments realized during the transition from the com. MOLCAS product to the open-source platform. The paper initially describes the tech. details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space SCF, d. matrix renormalization group (DMRG) methods, and hybrid multiconfigurational wave function and d. functional theory models. Some of these implementations include an array of addnl. options and functionalities. The paper proceeds and describes developments related to explorations of potential energy surfaces. Here we present methods for the optimization of conical intersections, the simulation of adiabatic and nonadiabatic mol. dynamics, and interfaces to tools for semiclassical and quantum mech. nuclear dynamics. Furthermore, the Article describes features unique to simulations of spectroscopic and magnetic phenomena such as the exact semiclassical description of the interaction between light and matter, various X-ray processes, magnetic CD, and properties. Finally, the paper describes a no. of built-in and add-on features to support the OpenMolcas platform with postcalcn. anal. and visualization, a multiscale simulation option using frozen-d. embedding theory, and new electronic and muonic basis sets.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhslKisbzM&md5=8b7ad4e027cd26706579b8717897e8b4
97. 97
  Butler, K. T.; Davies, D. W.; Cartwright, H.; Isayev, O.; Walsh, A. Machine learning for molecular and materials science. Nature 2018, 559, 547– 555, DOI: 10.1038/s41586-018-0337-2
  [Crossref], [PubMed], [CAS], Google Scholar
  97
  Machine learning for molecular and materials science
  Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh; Isayev, Olexandr; Walsh, Aron
  Nature (London, United Kingdom) (2018), 559 (7715), 547-555CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
  Here we summarize recent progress in machine learning for the chem. sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of mols. and materials is accelerated by artificial intelligence.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtl2jt7vL&md5=13d36f27db8d59f558fe28e946b4b009
98. 98
  Anderson, R.; Biong, A.; Gómez-Gualdrón, D. A. Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model. J. Chem. Theory Comput. 2020, 16, 1271– 1283, DOI: 10.1021/acs.jctc.9b00940
  [ACS Full Text ], [CAS], Google Scholar
  98
  Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model
  Anderson, Ryther; Biong, Achay; Gomez-Gualdron, Diego A.
  Journal of Chemical Theory and Computation (2020), 16 (2), 1271-1283CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  Tailoring the structure and chem. of metal-org. frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), mol. simulation has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent expts. to focus only on a small subset of the most promising MOFs. In many instances, however, even mol. simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede mol. simulation efforts. In this study, as a proof of concept, we trained a neural network - specifically, a multilayer perceptron (MLP) - as the first example of a machine learning model capable of predicting full adsorption isotherms of different mols. not included in the training of the model. To achieve this, we trained our MLP on "alchem." species, represented only by variables derived from their force field parameters, to predict the loadings of real adsorbates. MOFs were also represented by simple descriptors (e.g. geometric properties and chem. moieties). Alchem. species used for training were small, near-spherical, and nonpolar, enabling the prediction of analogous real mols. relevant for chem. sepns. such as argon, krypton, xenon, methane, ethane, and nitrogen. The trained model was shown to make accurate adsorption predictions for these six adsorbates in both hypothetical and existing MOFs. The MLP presented here is not expected to be applied "as is" to more complex adsorbates with properties not considered during its training. However, our results illustrate a new philosophy of training that can be built upon with the goal of predicting adsorption isotherms in not only a database of MOFs, but also for a database of adsorbates, and over a range of relevant operating conditions.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXnsl2gtA%253D%253D&md5=1294e3fa83333f3f2e91f212d8d12502
99. 99
  Borboudakis, G.; Stergiannakos, T.; Frysali, M.; Klontzas, E.; Tsamardinos, I.; Froudakis, G. E. Chemically intuited, large-scale screening of MOFs by machine learning techniques. npj Comput. Mater. 2017, 3, 40, DOI: 10.1038/s41524-017-0045-8
  [Crossref], Google Scholar
  There is no corresponding record for this reference.
100. 100
  Fanourgakis, G. S.; Gkagkas, K.; Tylianakis, E.; Klontzas, E.; Froudakis, G. A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials. J. Phys. Chem. A 2019, 123, 6080– 6087, DOI: 10.1021/acs.jpca.9b03290
  [ACS Full Text ], [CAS], Google Scholar
  100
  A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials
  Fanourgakis, George S.; Gkagkas, Konstantinos; Tylianakis, Emmanuel; Klontzas, Emmanuel; Froudakis, George
  Journal of Physical Chemistry A (2019), 123 (28), 6080-6087CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
  In the present study, we propose a new set of descriptors that, along with a few structural features of nanoporous materials, can be used by machine learning algorithms for accurate predictions of the gas uptake capacities of these materials. All new descriptors closely resemble the helium atom void fraction of the material framework. However, instead of a helium atom, a particle with an appropriately defined van der Waals radius is used. The set of void fractions of a small no. of these particles is found to be sufficient to characterize uniquely the structure of each material and to account for the most important topol. features. We assess the accuracy of our approach by examg. the predictions of the random forest algorithm in the relative small dataset of the computation-ready, exptl. (CoRE) MOFs (∼4700 structures) that have been exptl. synthesized and whose geometrical/structural features have been accurately calcd. before. We first performed grand canonical Monte Carlo simulations to accurately det. their methane uptake capacities at two different temps. (280 and 298 K) and three different pressures (1, 5.8, and 65 bar). Despite the high chem. and structural diversity of the CoRE MOFs, it was found that the use of the proposed descriptors significantly improves the accuracy of the machine learning algorithm, particularly at low pressures, compared to the predictions made based solely on the rest structural features. More importantly, the algorithm can be easily adapted for other types of nanoporous materials beyond MOFs. Convergence of the predictions was reached even for small training set sizes compared to what was found in previous works using the hypothetical MOF database.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhtFaqs7zL&md5=bc12ae914f0e452aa0d178a6f65ce673
101. 101
  Korolev, V.; Mitrofanov, A.; Korotcov, A.; Tkachenko, V. Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability. J. Chem. Inf. Model. 2020, 60, 22– 28, DOI: 10.1021/acs.jcim.9b00587
  [ACS Full Text ], [CAS], Google Scholar
  101
  Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability
  Korolev, Vadim; Mitrofanov, Artem; Korotcov, Alexandru; Tkachenko, Valery
  Journal of Chemical Information and Modeling (2020), 60 (1), 22-28CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
  Nowadays the development of new functional materials/chem. compds. using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chem. structure representation. The classical approach of rigorous feature engineering in ML typically improves the performance of the predictive model, but at the same time, it narrows down the scope of applicability and decreases the phys. interpretability of predicted results. In this study, we present graph convolutional neural networks (GCNNs) as an architecture that allows for successfully predicting the properties of compds. from diverse domains of chem. space, using a minimal set of meaningful descriptors. The applicability of GCNN models has been demonstrated by a wide range of chem. domain-specific properties. Their performance is comparable to state-of-the-art techniques; however, this architecture exempts from the need to carry out precise feature engineering.
  >> More from SciFinder ^®
  https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXisVGhtb3K&md5=04c9ffece81627cb0c2bdf8d2afccfda
102. 102
  Kapelewski, M. T.; Runčevski, T.; Tarver, J. D.; Jiang, H. Z.; Hurst, K. E.; Parilla, P. A.;

All Types

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Article Views

Altmetric

Citations

Abstract

Synopsis

Introduction

Figure 1

Figure 2

Databases of Nanoporous Materials

Curated Structures from Experimental Syntheses

Hypothetical Structures

Computation of Materials’ Properties

Gas Adsorption Properties

Open Challenges

Ranking Materials

Toward Best Practices

Reproducibility

Automation

Open Source

Setting the Stage for Machine Learning

Toward a Prototype of a Materials Matching Platform

Figure 3

Figure 4

Figure 5

Figure 6

Author Information

Acknowledgments

Acronyms

References

Cited By

Abstract

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

References