Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic FingerprintsClick to copy article linkArticle link copied!
- Olexandr Isayev
- Denis Fourches
- Eugene N. Muratov
- Corey Oses
- Kevin Rasch
- Alexander Tropsha
- Stefano Curtarolo
Abstract
As the proliferation of high-throughput approaches in materials science is increasing the wealth of data in the field, the gap between accumulated-information and derived-knowledge widens. We address the issue of scientific discovery in materials databases by introducing novel analytical approaches based on structural and electronic materials fingerprints. The framework is employed to (i) query large databases of materials using similarity concepts, (ii) map the connectivity of materials space (i.e., as a materials cartograms) for rapidly identifying regions with unique organizations/properties, and (iii) develop predictive Quantitative Materials Structure–Property Relationship models for guiding materials design. In this study, we test these fingerprints by seeking target material properties. As a quantitative example, we model the critical temperatures of known superconductors. Our novel materials fingerprinting and materials cartography approaches contribute to the emerging field of materials informatics by enabling effective computational tools to analyze, visualize, model, and design new materials.
Introduction
Methods
AFLOWLIB Library and Data
Data set of Superconducting Materials
Materials Fingerprints
Figure 1
Figure 1. Construction of materials fingerprints from the band structure and the density of states. For simplicity, we illustrate the idea of B-fingerprints with only 8 bins.
B-Fingerprint
D-Fingerprint
SiRMS Descriptors for Materials
Figure 2
Figure 2. Generation of SiRMS descriptors for materials.
Network Representation (Material Cartograms)
Results and Discussion
Similarity Search in the Materials Space
Visualizing and Exploring the Materials Space
Figure 3
Figure 3. Materials cartograms with D- (top) and B-fingerprint network representations (bottom). (a) D-fingerprint network representation of materials. Materials are colored according to the number of atoms per unit cell. Regions corresponding to pure elements, binary, ternary, and quaternary compounds are outlined. (b) Distribution of connectivity within the network. (c) Mapping band gaps of materials. Points colored in deep blue are metals; insulators are colored according to the band gap value. Four large communities are outlined. (d) Mapping the superconductivity critical temperature, Tc, with relevant regions outlined.
Figure 4
Figure 4. Comparison high-low Tc aligned band structures and Tc predictions. (a) Band structure for Ba2Ca2Cu3HgO8, Tc = 133 K. (b) Band structure of SrCuO2 (ICSD No. 16217, Tc = 91 K). (74) (c) Aligned B-fingerprints for the 15 materials with the highest and lowest Tc. (d) Band structure of Nb2Se3 (ICSD No. 42981, Tc = 0.4 K). (e) Plot of the predicted vs experimental critical temperatures for the continuous model. Materials are color-coded according to the classification model: solid/open green (red) circles indicate correct/incorrect predictions in Tc > Tthr (Tc ≤ Tthr), respectively.
Predictive QMSPR Modeling
Continuous Model
Classification Model
Figure 5
Figure 5. Materials color-coded according to atom contributions to log(Tc). Atoms and structural fragments that decrease superconductivity critical temperatures are colored in red and those enhancing Tc are shown in green. Uninfluential fragments are in gray. (a) Ba2Ca2Cu3HgO8; (b) As2Ni2O6Sc2Sr4; (c) Mo6PbS8; (d) Mo6NdS8; (e) Li2Pd3B; (f) Li2Pt3B; (g) FeLaAsO; (h) FeLaPO.
Structural Model
Conclusion
Supporting Information
Additional statistical information relevant to the materials cartograms and all three models (continuous, classification, and structural). This material is available free of charge via the Internet at http://pubs.acs.org.
Terms & Conditions
Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.
Acknowledgment
We thank Drs. Marco Buongiorno Nardelli, Stefano Sanvito, Ohad Levy, Amir Natan, Gus Hart, Allison Stelling, Luis Agapito, and Cheng-Ing Chia for various technical discussions that have contributed to the results reported in this article. A.T. acknowledges support from DOD-ONR (N00014-13-1-0028), ITS Research Computing Center at UNC, and the Russian Scientific Foundation (No. 14-43-00024) for partial support. S.C. acknowledges support from DOD-ONR (N00014-13-1-0030, N00014-13-1-0635), DOE (DE-AC02-05CH11231, specifically BES Grant No. EDCBEE), and the Duke University Center for Materials Genomics. C.O. acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant No. DGF1106401. We also acknowledge the CRAY corporation for computational support.
References
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- 27Curtarolo, S.; Setyawan, W.; Hart, G. L. W.; Jahnatek, M.; Chepulskii, R. V.; Taylor, R. H.; Wang, S.; Xue, J.; Yang, K.; Levy, O.; Mehl, M.; Stokes, H. T.; Demchenko, D. O.; Morgan, D. Comput. Mater. Sci. 2012, 58, 218– 226Google Scholar27https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktL8%253D&md5=8129bab53c054672274b0d6fa64172efAFLOW: An automatic framework for high-throughput materials discoveryCurtarolo, 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, DaneComputational 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.
- 28Curtarolo, S.; Setyawan, W.; Wang, S.; Xue, J.; Yang, K.; Taylor, R. H.; Nelson, L. J.; Hart, G. L. W.; Sanvito, S.; Buongiorno Nardelli, M.; Mingo, N.; Levy, O. Comput. Mater. Sci. 2012, 58, 227– 235Google Scholar28https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktLw%253D&md5=1fc77b7de60ced338e5f3145f3cea020AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculationsCurtarolo, Stefano; Setyawan, Wahyu; Wang, Shidong; Xue, Junkai; Yang, Kesong; Taylor, Richard H.; Nelson, Lance J.; Hart, Gus L. W.; Sanvito, Stefano; Buongiorno-Nardelli, Marco; Mingo, Natalio; Levy, OhadComputational Materials Science (2012), 58 (), 227-235CODEN: CMMSEM; ISSN:0927-0256. (Elsevier B.V.)Empirical databases of crystal structures and thermodn. properties are fundamental tools for materials research. Recent rapid proliferation of computational data on materials properties presents the possibility to complement and extend the databases where the exptl. data is lacking or difficult to obtain. Enhanced repositories that integrate both computational and empirical approaches open novel opportunities for structure discovery and optimization, including uncovering of unsuspected compds., metastable structures and correlations between various characteristics. The practical realization of these opportunities depends on a systematic compilation and classification of the generated data in addn. to an accessible interface for the materials science community. In this paper we present an extensive repository, aflowlib.org, comprising phase-diagrams, electronic structure and magnetic properties, generated by the high-throughput framework AFLOW. This continuously updated compilation currently contains over 150,000 thermodn. entries for alloys, covering the entire compn. range of more than 650 binary systems, 13,000 electronic structure analyses of inorg. compds., and 50,000 entries for novel potential magnetic and spintronics systems. The repository is available for the scientific community on the website of the materials research consortium, aflowlib.org.
- 29Kresse, G.; Furthmüller, J. Comput. Mater. Sci. 1996, 6, 15Google Scholar29https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmtFWgsrk%253D&md5=779b9a71bbd32904f968e39f39946190Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis setKresse, G.; Furthmuller, J.Computational Materials Science (1996), 6 (1), 15-50CODEN: CMMSEM; ISSN:0927-0256. (Elsevier)The authors present a detailed description and comparison of algorithms for performing ab-initio quantum-mech. calcns. using pseudopotentials and a plane-wave basis set. The authors will discuss: (a) partial occupancies within the framework of the linear tetrahedron method and the finite temp. d.-functional theory, (b) iterative methods for the diagonalization of the Kohn-Sham Hamiltonian and a discussion of an efficient iterative method based on the ideas of Pulay's residual minimization, which is close to an order N2atoms scaling even for relatively large systems, (c) efficient Broyden-like and Pulay-like mixing methods for the charge d. including a new special preconditioning optimized for a plane-wave basis set, (d) conjugate gradient methods for minimizing the electronic free energy with respect to all degrees of freedom simultaneously. The authors have implemented these algorithms within a powerful package called VAMP (Vienna ab-initio mol.-dynamics package). The program and the techniques have been used successfully for a large no. of different systems (liq. and amorphous semiconductors, liq. simple and transition metals, metallic and semi-conducting surfaces, phonons in simple metals, transition metals and semiconductors) and turned out to be very reliable.
- 30Blöchl, P. E. Phys. Rev. B 1994, 50, 17953– 17979Google Scholar30https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2sfjslSntA%253D%253D&md5=1853d67af808af2edab58beaab5d3051Projector augmented-wave methodBlochlPhysical review. B, Condensed matter (1994), 50 (24), 17953-17979 ISSN:0163-1829.There is no expanded citation for this reference.
- 31Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865– 3868Google Scholar31https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmsVCgsbs%253D&md5=55943538406ee74f93aabdf882cd4630Generalized gradient approximation made simplePerdew, John P.; Burke, Kieron; Ernzerhof, MatthiasPhysical Review Letters (1996), 77 (18), 3865-3868CODEN: PRLTAO; ISSN:0031-9007. (American Physical Society)Generalized gradient approxns. (GGA's) for the exchange-correlation energy improve upon the local spin d. (LSD) description of atoms, mols., and solids. We present a simple derivation of a simple GGA, in which all parameters (other than those in LSD) are fundamental consts. Only general features of the detailed construction underlying the Perdew-Wang 1991 (PW91) GGA are invoked. Improvements over PW91 include an accurate description of the linear response of the uniform electron gas, correct behavior under uniform scaling, and a smoother potential.
- 32Taylor, R. H.; Rose, F.; Toher, C.; Levy, O.; Yang, K.; Buongiorno Nardelli, M.; Curtarolo, S. Comput. Mater. Sci. 2014, 93, 178– 192Google ScholarThere is no corresponding record for this reference.
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- 36Fourches, D.; Muratov, E.; Tropsha, A. J. Chem. Inf. Model. 2010, 50, 1189– 1204Google Scholar36https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXnvVeitLk%253D&md5=4c19d67a67094bc595f5940157ff9a2dTrust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling ResearchFourches, Denis; Muratov, Eugene; Tropsha, AlexanderJournal of Chemical Information and Modeling (2010), 50 (7), 1189-1204CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)With the recent advent of high-throughput technologies for both compd. synthesis and biol. screening, there is no shortage of publicly or com. available data sets and databases that can be used for computational drug discovery applications. Rapid growth of large, publicly available databases (such as PubChem or ChemSpider contg. more than 20 million mol. records each) enabled by exptl. projects such as NIH's Mol. Libraries and Imaging Initiative provides new opportunities for the development of chemoinformatics methodologies and their application to knowledge discovery in mol. databases. A fundamental assumption of any chemoinformatics study is the correctness of the input data generated by exptl. scientists and available in various data sets. In another recent study, the authors investigated several public and com. databases to calc. their error rates: the latter were ranging from 0.1 to 3.4% depending on the database. How significant is the problem of accurate structure representation (given that the error rates in current databases may appear relatively low) since it concerns exploratory chemoinformatics and mol. modeling research. Recent investigations by a large group of collaborators from six labs. have clearly demonstrated that the type of chem. descriptors has much greater influence on the prediction performance of QSAR models than the nature of model optimization techniques.
- 37Valle, M.; Oganov, A. R. Acta Crystallogr., Sect. A 2010, 66, 507– 517Google Scholar37https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtVeku7rO&md5=056854820ccfe748ead520f5dc93b967Crystal fingerprint space - a novel paradigm for studying crystal-structure setsValle, Mario; Oganov, Artem R.Acta Crystallographica, Section A: Foundations of Crystallography (2010), 66 (5), 507-517CODEN: ACACEQ; ISSN:0108-7673. (International Union of Crystallography)The initial aim of the crystal fingerprint project was to solve a very specific problem: to classify and remove duplicate crystal structures from the results generated by the evolutionary crystal-structure predictor USPEX. These duplications decrease the genetic diversity of the population used by the evolutionary algorithm, potentially leading to stagnation and, after a certain time, reducing the likelihood of predicting essentially new structures. After solving the initial problem, the approach led to unexpected discoveries: unforeseen correlations, useful derived quantities and insight into the structure of the overall set of results. All of these were facilitated by the project's underlying idea: to transform the structure sets from the phys. configuration space to an abstr., high-dimensional space called the fingerprint space. Here every structure is represented as a point whose coordinates (fingerprint) are computed from the crystal structure. Then the space's distance measure, interpreted as structure 'closeness', enables grouping of structures into similarity classes. This model provides much flexibility and facilitates access to knowledge and algorithms from fields outside crystallog., e.g. pattern recognition and data mining. The current usage of the fingerprint-space model is revealing interesting properties that relate to chem. and crystallog. attributes of a structure set. For this reason, the mapping of structure sets to fingerprint space could become a new paradigm for studying crystal-structure ensembles and global chem. features of the energy landscape.
- 38Kuz’min, V. E.; Artemenko, A. G.; Muratov, E. N. J. Comp.-Aided Mol. Des. 2008, 22, 403– 421Google Scholar38https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXmtVSnt7Y%253D&md5=e8a6a3085289532d90423d6ee43cd5c1Hierarchical QSAR technology based on the Simplex representation of molecular structureKuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.Journal of Computer-Aided Molecular Design (2008), 22 (6-7), 403-421CODEN: JCADEQ; ISSN:0920-654X. (Springer)This article is about the hierarchical quant. structure-activity relationship technol. (HiT QSAR) based on the Simplex representation of mol. structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technol. is a sequential soln. (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of mol. structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solns. In the SiRMS approach, every mol. is represented as a system of different simplexes (tetrat. fragments with fixed compn., structure, chirality and symmetry). The level of simplex descriptors detailing increases consecutively from the 1D to 4D representation of the mol. structure. The advantages of the approach reported here are the absence of "mol. alignment" problems, consideration of different phys.-chem. properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for mol. design. The efficiency of the HiT QSAR approach is demonstrated by comparing it with the most popular modern QSAR approaches on two representative examn. sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the mol. structure description are also highlighted. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biol. expts., among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a no. of useful utilities.
- 39Muratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Nikolaeva-Glomb, L.; Galabov, A. S.; Kuz’min, V. E. Struct Chem. 2013, 24, 1665– 1679Google Scholar39https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsV2mtbbK&md5=239c8a803bc3cc9b1005fd51f9a8abd5QSAR analysis of poliovirus inhibition by dual combinations of antiviralsMuratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Nikolaeva-Glomb, L.; Galabov, A. S.; Kuz'min, V. E.Structural Chemistry (2013), 24 (5), 1665-1679CODEN: STCHES; ISSN:1040-0400. (Springer)We have applied Hierarchical QSAR Technol. (HiT QSAR) to the prediction of antiviral effects of paired combinations of picornavirus replication inhibitors against poliovirus 1 (Mahoney) in vitro. The inhibition from all binary combinations of eight antivirals were investigated. Simplex representation of mol. structure (SiRMS) was used for the generation of mol. descriptors of both pure compds. and all dual mixt. combinations. Predictive QSAR models were obtained using the partial least squares (PLS) method. Predictive power of the developed models was validated using eightfold external cross-validation (CV, Q2ext = 0.67-0.93). Adequate models (Q2ext = 0.53-0.97) were obtained in the same way for predicting measured inhibitory concns. at other levels (i.e., IC30, IC40, IC60, IC70). The usage of predicted values of these concns. in the framework of the feature net (FN) approach led to an insignificant increase in the quality of the obtained QSAR models (Q2ext = 0.71-0.94). Developed QSAR models were analyzed and interpreted so that structural fragments and components of the combination promoting the antiviral activity were detd. (e.g., 2-(4-methoxyphenyl)-4,5-dihydrooxazole or the combination of N-hydroxybenzimidoyl and 3-methylisoxazole). Then the resulting consensus model was used to predict novel potent combinations of drugs. Combinations of enviroxime with pleconaril, WIN52084, and rupintrivir and the mixt. of rupintrivir with disoxaril were predicted to cause the most inhibition of poliovirus 1 replication. HiT QSAR proved itself as an adequate tool for QSAR anal. of mixts. and, although the method described here is suitable only for binary mixts., it can be easily extended for more complex combinations.
- 40Muratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Kuz’min, V. E. Mol. Inf. 2012, 31, 202– 221Google Scholar40https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xjs1ygtrw%253D&md5=734a57799a1ae99089874916bad263b0Existing and Developing Approaches for QSAR Analysis of MixturesMuratov, Eugene N.; Varlamova, Ekaterina V.; Artemenko, Anatoly G.; Polishchuk, Pavel G.; Kuz'min, Victor E.Molecular Informatics (2012), 31 (3-4), 202-221CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)This review is devoted to the crit. anal. of advantages and disadvantages of existing mixt. descriptors and their usage in various QSAR/QSPR tasks. We describe good practices for the QSAR modeling of mixts., data sources for mixts., a discussion of various mixt. descriptors and their application, recommendations about proper external validation specific for mixt. QSAR modeling, and future perspectives of this field. The biggest problem in QSAR of mixts. is the lack of reliable data about the mixts.' properties. Various mixt. descriptors are used for the modeling of different endpoints. However, these descriptors have certain disadvantages, such as applicability only to 1 : 1 binary mixts., and additive nature. The field of QSAR of mixts. is still under development, and existing efforts could be considered as a foundation for future approaches and studies. The usage of non-additive mixt. descriptors, which are sensitive to interaction effects, in combination with best practices of QSAR model development (e.g., thorough data collection and curation, rigorous external validation, etc.) will significantly improve the quality of QSAR studies of mixts.
- 41Bastian, M.; Heymann, S.; Jacomy, M. Int. Conf. Weblogs Social Media 2009, 8, 361– 362Google ScholarThere is no corresponding record for this reference.
- 42Jacomy, M.; Venturini, T.; Heymann, S.; Bastian, M. PLoS One 2014, 9, e98679Google ScholarThere is no corresponding record for this reference.
- 43Hedin, L. Phys. Rev. 1965, 139, A796– A823Google ScholarThere is no corresponding record for this reference.
- 44Aryasetiawan, F.; Gunnarsson, O. Rep. Prog. Phys. 1998, 61, 237Google Scholar44https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXitlWktLw%253D&md5=a0a95f38d413d7c09a71e3c637331dcaThe GW methodAryasetiawan, F.; Gunnarsson, O.Reports on Progress in Physics (1998), 61 (3), 237-312CODEN: RPPHAG; ISSN:0034-4885. (Institute of Physics Publishing)A review with many refs. Calcns. of ground-state and excited-state properties of materials have been one of the major goals of condensed matter physics. Ground-state properties of solids have been extensively investigated for several decades within the std. d. functional theory. Excited-state properties, on the other hand, were relatively unexplored in ab initio calcns. until a decade ago. The most suitable approach up to now for studying excited-state properties of extended systems is the Green function method. To calc. the Green function one requires the self-energy operator which is non-local and energy dependent. In this article we describe the GW approxn. which has turned out to be a fruitful approxn. to the self-energy. The Green function theory, numerical methods for carrying out the self-energy calcns., simplified schemes, and applications to various systems are described. Self-consistency issues and new developments beyond the GW approxn. are also discussed as well as the success and shortcomings of the GW approxn.
- 45Heyd, J.; Scuseria, G. E.; Ernzerhof, M. J. Chem. Phys. 2003, 118, 8207– 8215Google Scholar45https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXjtlSisLw%253D&md5=05a44dc5890abc3dfa8e1ef5338a4781Hybrid functionals based on a screened Coulomb potentialHeyd, Jochen; Scuseria, Gustavo E.; Ernzerhof, MatthiasJournal of Chemical Physics (2003), 118 (18), 8207-8215CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Hybrid d. functionals are very successful in describing a wide range of mol. properties accurately. In large mols. and solids, however, calcg. the exact (Hartree-Fock) exchange is computationally expensive, esp. for systems with metallic characteristics. In the present work, we develop a new hybrid d. functional based on a screened Coulomb potential for the exchange interaction which circumvents this bottleneck. The results obtained for structural and thermodn. properties of mols. are comparable in quality to the most widely used hybrid functionals. In addn., we present results of periodic boundary condition calcns. for both semiconducting and metallic single wall carbon nanotubes. Using a screened Coulomb potential for Hartree-Fock exchange enables fast and accurate hybrid calcns., even of usually difficult metallic systems. The high accuracy of the new screened Coulomb potential hybrid, combined with its computational advantages, makes it widely applicable to large mols. and periodic systems.
- 46Liechtenstein, A. I.; Anisimov, V. I.; Zaanen, J. Phys. Rev. B 1995, 52, R5467– R5470Google ScholarThere is no corresponding record for this reference.
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- 52Bhalla, A. S.; Guo, R.; Roy, R. Mater. Res. Innovat. 2000, 4, 3– 26Google Scholar52https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXitVGqtw%253D%253D&md5=9d0450b768ef026ffb4183b2d74de8ffThe perovskite structure - a review of its role in ceramic science and technologyBhalla, A. S.; Guo, Ruyan; Roy, RustumMaterials Research Innovations (2000), 4 (1), 3-26CODEN: MRINFV; ISSN:1432-8917. (Springer-Verlag)A review with 107 refs. Starting with the history of the fundamental science of the relation of structure to compn. delineated completely by Goldschmidt, we use the perovskite structure to illustrate the enormous power of crystal chem.-based intelligent synthesis in creating new materials. The perovskite structure is shown to be the single most versatile ceramic host. By appropriate changes in compn. one can modify the most significant electroceramic dielec. (BaTiO3 and its relatives) phase in industry, into metallic conductors, superconductors or the highest pressure phases in the earth. After an historical introduction of the science, detailed treatment of the applications is confined to the most recent research on novel uses in piezoelec., ferroelec. and related applications.
- 53Rabe, K. M.; Ahn, C. H.; Triscone, J. M. Physics of Ferroelectrics: A Modern Perspective; Springer: New York, 2010.Google ScholarThere is no corresponding record for this reference.
- 54Yang, K.; Setyawan, W.; Wang, S.; Buongiorno Nardelli, M.; Curtarolo, S. Nat. Mater. 2012, 11, 614– 619Google ScholarThere is no corresponding record for this reference.
- 55Hasan, M. Z.; Kane, C. L. Rev. Mod. Phys. 2010, 82, 3045– 3067Google Scholar55https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht1Kgsg%253D%253D&md5=4dd1d199f00e448af7ec5420a23d845fColloquium: topological insulatorsHasan, M. Z.; Kane, C. L.Reviews of Modern Physics (2010), 82 (4), 3045-3067CODEN: RMPHAT; ISSN:0034-6861. (American Physical Society)A review. Topol. insulators are electronic materials that have a bulk band gap like an ordinary insulator but have protected conducting states on their edge or surface. These states are possible due to the combination of spin-orbit interactions and time-reversal symmetry. The two-dimensional (2D) topol. insulator is a quantum spin Hall insulator, which is a close cousin of the integer quantum Hall state. A three-dimensional (3D) topol. insulator supports novel spin-polarized 2D Dirac fermions on its surface. In this Colloquium the theor. foundation for topol. insulators and superconductors is reviewed and recent expts. are described in which the signatures of topol. insulators have been obsd. Transport expts. on HgTe/CdTe quantum wells are described that demonstrate the existence of the edge states predicted for the quantum spin Hall insulator. Expts. on Bi1-xSbx, Bi2Se3, Bi2Te3, and Sb2Te3 are then discussed that establish these materials as 3D topol. insulators and directly probe the topol. of their surface states. Exotic states are described that can occur at the surface of a 3D topol. insulator due to an induced energy gap. A magnetic gap leads to a novel quantum Hall state that gives rise to a topol. magnetoelec. effect. A superconducting energy gap leads to a state that supports Majorana fermions and may provide a new venue for realizing proposals for topol. quantum computation. Prospects for observing these exotic states are also discussed, as well as other potential device applications of topol. insulators.
- 56Chen, Y. L.; Analytis, J. G.; Chu, J.-H.; Liu, Z. K.; Mo, S.-K.; Qi, X.-L.; Zhang, H.-J.; Lu, D. H.; Dai, X.; Fang, Z.; Zhang, S.-C.; Fisher, I. R.; Hussain, Z.; Shen, Z.-X. Science 2009, 325, 178– 181Google Scholar56https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXos1Srsbc%253D&md5=5d9c228c5a47d2348f4821fa4cbb1beeExperimental realization of a three-dimensional topological insulator, Bi2Te3Chen, Y. L.; Analytis, J. G.; Chu, J.-H.; Liu, Z. K.; Mo, S.-K.; Qi, X. L.; Zhang, H. J.; Lu, D. H.; Dai, X.; Fang, Z.; Zhang, S. C.; Fisher, I. R.; Hussain, Z.; Shen, Z.-X.Science (Washington, DC, United States) (2009), 325 (5937), 178-181CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)Three-dimensional topol. insulators are a state of quantum matter with a bulk gap and odd no. of relativistic Dirac fermions on the surface. From investigating the surface state of Bi2Te3 with angle-resolved photoemission spectroscopy, the surface state consists of a single non-degenerate Dirac cone. Furthermore, with appropriate hole doping, the Fermi level can be tuned to intersect only the surface states and indicate a full energy gap for the bulk states. Bi2Te3 is a simple model system for the three-dimensional topol. insulator with a single Dirac cone on the surface. The large bulk gap of Bi2Te3 also points to promising potential for high-temp. spintronics applications.
- 57Zhang, T.; Cheng, P.; Chen, X.; Jia, J.-F.; Ma, X.; He, K.; Wang, L.; Zhang, H.; Dai, X.; Fang, Z.; Xie, X.; Xue, Q.-K. Phys. Rev. Lett. 2009, 103, 266803Google ScholarThere is no corresponding record for this reference.
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- 59Arakane, T.; Sato, T.; Souma, S.; Kosaka, K.; Nakayama, K.; Komatsu, M.; Takahashi, T.; Ren, Z.; Segawa, K.; Ando, Y. Nat. Commun. 2012, 3, 636Google Scholar59https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC387otVemtA%253D%253D&md5=5f5623a5561ad4c9f328831c3ab2a7b9Tunable Dirac cone in the topological insulator Bi(2-x)Sb(x)Te(3-y)Se(y)Arakane T; Sato T; Souma S; Kosaka K; Nakayama K; Komatsu M; Takahashi T; Ren Zhi; Segawa Kouji; Ando YoichiNature communications (2012), 3 (), 636 ISSN:.The three-dimensional topological insulator is a quantum state of matter characterized by an insulating bulk state and gapless Dirac cone surface states. Device applications of topological insulators require a highly insulating bulk and tunable Dirac carriers, which has so far been difficult to achieve. Here we demonstrate that Bi(2-x)Sb(x)Te(3-y)Se(y) is a system that simultaneously satisfies both of these requirements. For a series of compositions presenting bulk-insulating transport behaviour, angle-resolved photoemission spectroscopy reveals that the chemical potential is always located in the bulk band gap, whereas the Dirac cone dispersion changes systematically so that the Dirac point moves up in energy with increasing x, leading to a sign change of the Dirac carriers at x~0.9. Such a tunable Dirac cone opens a promising pathway to the development of novel devices based on topological insulators.
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Abstract
Figure 1
Figure 1. Construction of materials fingerprints from the band structure and the density of states. For simplicity, we illustrate the idea of B-fingerprints with only 8 bins.
Figure 2
Figure 2. Generation of SiRMS descriptors for materials.
Figure 3
Figure 3. Materials cartograms with D- (top) and B-fingerprint network representations (bottom). (a) D-fingerprint network representation of materials. Materials are colored according to the number of atoms per unit cell. Regions corresponding to pure elements, binary, ternary, and quaternary compounds are outlined. (b) Distribution of connectivity within the network. (c) Mapping band gaps of materials. Points colored in deep blue are metals; insulators are colored according to the band gap value. Four large communities are outlined. (d) Mapping the superconductivity critical temperature, Tc, with relevant regions outlined.
Figure 4
Figure 4. Comparison high-low Tc aligned band structures and Tc predictions. (a) Band structure for Ba2Ca2Cu3HgO8, Tc = 133 K. (b) Band structure of SrCuO2 (ICSD No. 16217, Tc = 91 K). (74) (c) Aligned B-fingerprints for the 15 materials with the highest and lowest Tc. (d) Band structure of Nb2Se3 (ICSD No. 42981, Tc = 0.4 K). (e) Plot of the predicted vs experimental critical temperatures for the continuous model. Materials are color-coded according to the classification model: solid/open green (red) circles indicate correct/incorrect predictions in Tc > Tthr (Tc ≤ Tthr), respectively.
Figure 5
Figure 5. Materials color-coded according to atom contributions to log(Tc). Atoms and structural fragments that decrease superconductivity critical temperatures are colored in red and those enhancing Tc are shown in green. Uninfluential fragments are in gray. (a) Ba2Ca2Cu3HgO8; (b) As2Ni2O6Sc2Sr4; (c) Mo6PbS8; (d) Mo6NdS8; (e) Li2Pd3B; (f) Li2Pt3B; (g) FeLaAsO; (h) FeLaPO.
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- 8Setyawan, W.; Gaume, R. M.; Lam, S.; Feigelson, R. S.; Curtarolo, S. ACS Comb. Sci. 2011, 13, 382– 3908https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXns1enur0%253D&md5=b8b239d200ac996312c39dfe5d0ca975High-Throughput Combinatorial Database of Electronic Band Structures for Inorganic Scintillator MaterialsSetyawan, Wahyu; Gaume, Romain M.; Lam, Stephanie; Feigelson, Robert S.; Curtarolo, StefanoACS Combinatorial Science (2011), 13 (4), 382-390CODEN: ACSCCC; ISSN:2156-8944. (American Chemical Society)For the purpose of creating a database of electronic structures of all the known inorg. compds., we have developed a computational framework based on high-throughput ab initio calcns. (AFLOW) and an online repository (www.aflowlib.org). In this article, we report the first step of this task: the calcn. of band structures for 7439 compds. intended for the research of scintillator materials for γ-ray radiation detection. Data-mining is performed to select the candidates from 193 456 compds. compiled in the Inorg. Crystal Structure Database. Light yield and scintillation nonproportionality are predicted based on semiempirical band gaps and effective masses. We present a list of materials, potentially bright and proportional, and focus on those exhibiting small effective masses and effective mass ratios.
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- 10Hachmann, J.; Olivares-Amaya, R.; Atahan-Evrenk, S.; Amador-Bedolla, C.; Sánchez-Carrera, R. S.; Gold-Parker, A.; Vogt, L.; Brockway, A. M.; Aspuru-Guzik, A. J. Phys. Chem. Lett. 2011, 2, 2241– 225110https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtVKht7rK&md5=68f7f2d3a8a5b5fe6cb2c3b677f444bfThe Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community GridHachmann, Johannes; Olivares-Amaya, Roberto; Atahan-Evrenk, Sule; Amador-Bedolla, Carlos; Sanchez-Carrera, Roel S.; Gold-Parker, Aryeh; Vogt, Leslie; Brockway, Anna M.; Aspuru-Guzik, AlanJournal of Physical Chemistry Letters (2011), 2 (17), 2241-2251CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)This Perspective introduces the Harvard Clean Energy Project (CEP), a theory-driven search for the next generation of org. solar cell materials. We give a broad overview of its setup and infrastructure, present first results, and outline upcoming developments. CEP has established an automated, high-throughput, in silico framework to study potential candidate structures for org. photovoltaics. The current project phase is concerned with the characterization of millions of mol. motifs using first-principles quantum chem. The scale of this study requires a correspondingly large computational resource, which is provided by distributed volunteer computing on IBM's World Community Grid. The results are compiled and analyzed in a ref. database and will be made available for public use. In addn. to finding specific candidates with certain properties, it is the goal of CEP to illuminate and understand the structure-property relations in the domain of org. electronics. Such insights can open the door to a rational and systematic design of future high-performance materials. The computational work in CEP is tightly embedded in a collaboration with experimentalists, who provide valuable input and feedback to the project.
- 11Hachmann, J.; Olivares-Amaya, R.; Jinich, A.; Appleton, A. L.; Blood-Forsythe, M. A.; Seress, L. R.; Román-Salgado, C.; Trepte, K.; Atahan-Evrenk, S.; Er, S.; Shrestha, S.; Mondal, R.; Sokolov, A.; Bao, Z.; Aspuru-Guzik, A. Energy Environ. Sci. 2014, 7, 698– 704There is no corresponding record for this reference.
- 12Materials Genome Initiative. Office of Science and Technology Policy, White House, http://www.whitehouse.gov/mgi 2011.There is no corresponding record for this reference.
- 13Suh, C.; Rajan, K. Mater. Sci. Technol. 2009, 25, 466– 47113https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXmtV2ntL0%253D&md5=2935bdde12c64100536c7dd2f4fb5493Data mining and informatics for crystal chemistry: establishing measurement techniques for mapping structure-property relationshipsSuh, C.; Rajan, K.Materials Science and Technology (2009), 25 (4), 466-471CODEN: MSCTEP; ISSN:0267-0836. (Maney Publishing)A review. The present paper demonstrates how data mining techniques can be used to quant. assess multivariate material properties, such as electronic features and crystal structure parameters. Using AB2N4 spinel nitrides as a template for the present study, the authors have assessed the statistical interdependency of each of the descriptors that may influence chem.-structure-property relationships of spinel nitrides. Using principal component anal., the authors demonstrate that classical versions of structure maps from the early work of Hill based on heuristic observations for this class of crystal chem. can in fact be reproduced via data mining. The informatics approach also provides an alternative method for visualizing structure maps as well as interpreting structure-property relationships. Apart from being able to reproduce earlier versions of structure maps, an example is also developed for the case of a new informatics based structure map for spinel nitrides, showing data clustering assocd. with site occupancy.
- 14Olivares-Amaya, R.; Amador-Bedolla, C.; Hachmann, J.; Atahan-Evrenk, S.; Sanchez-Carrera, R. S.; Vogt, L.; Aspuru-Guzik, A. Energy Environ. Sci. 2011, 4, 4849– 4861There is no corresponding record for this reference.
- 15Schuett, K. T.; Glawe, H.; Brockherde, F.; Sanna, A.; Mueller, K. R.; Gross, E. K. U. Phys. Rev. B 2014, 89, 205118There is no corresponding record for this reference.
- 16Seko, A.; Maekawa, T.; Tsuda, K.; Tanaka, I. Phys. Rev. B 2014, 89, 054303There is no corresponding record for this reference.
- 17Laggner, C.; Kokel, D.; Setola, V.; Tolia, A.; Lin, H.; Irwin, J. J.; Keiser, M. J.; Cheung, C. Y. J.; M, D. L., Jr.; Roth, B. L.; Peterson, R. T.; Shoichet, B. K. Nat. Chem. Biol. 2012, 8, 144– 14617https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhs1eitrvN&md5=9bc5080ef9e0eb7e0b9c6a49ced99b39Chemical informatics and target identification in a zebrafish phenotypic screenLaggner, Christian; Kokel, David; Setola, Vincent; Tolia, Alexandra; Lin, Henry; Irwin, John J.; Keiser, Michael J.; Cheung, Chung Yan J.; Minor, Daniel L.; Roth, Bryan L.; Peterson, Randall T.; Shoichet, Brian K.Nature Chemical Biology (2012), 8 (2), 144-146CODEN: NCBABT; ISSN:1552-4450. (Nature Publishing Group)Target identification is a core challenge in chem. genetics. Here we use chem. similarity to computationally predict the targets of 586 compds. that were active in a zebrafish behavioral assay. Among 20 predictions tested, 11 compds. had activities ranging from 1 nM to 10,000 nM on the predicted targets. The roles of two of these targets were tested in the original zebrafish phenotype. Prediction of targets from chemotype is rapid and may be generally applicable.
- 18Besnard, J.; Ruda, G. F.; Setola, V.; Abecassis, K.; Rodriquiz, R. M.; Huang, X. P.; Norval, S.; Sassano, M. F.; Shin, A. I.; Webster, L. A. Nature 2012, 492, 215– 220There is no corresponding record for this reference.
- 19Cherkasov, A.; Muratove, E. N.; Fourches, D.; Varnexk, A.; Baskin, I. I.; Cronin, M.; Dearden, J.; Gramatica, P.; Martin, Y. C.; Todeschini, R. J. Med. Chem. 2013, 57, 4977There is no corresponding record for this reference.
- 20Lusci, A.; Pollastri, G.; Baldi, P. J. Chem. Inf. Model. 2013, 53, 1563– 157520https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpvVGht7g%253D&md5=d51e537fea2f1f53ea5013224ee1cdc9Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like MoleculesLusci, Alessandro; Pollastri, Gianluca; Baldi, PierreJournal of Chemical Information and Modeling (2013), 53 (7), 1563-1575CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A review. Shallow machine learning methods have been applied to chemoinformatics problems with some success. As more data becomes available and more complex problems are tackled, deep machine learning methods may also become useful. Here, we present a brief overview of deep learning methods and show in particular how recursive neural network approaches can be applied to the problem of predicting mol. properties. However, mols. are typically described by undirected cyclic graphs, while recursive approaches typically use directed acyclic graphs. Thus, we develop methods to address this discrepancy, essentially by considering an ensemble of recursive neural networks assocd. with all possible vertex-centered acyclic orientations of the mol. graph. One advantage of this approach is that it relies only minimally on the identification of suitable mol. descriptors because suitable representations are learned automatically from the data. Several variants of this approach are applied to the problem of predicting aq. soly. and tested on four benchmark data sets. Exptl. results show that the performance of the deep learning methods matches or exceeds the performance of other state-of-the-art methods according to several evaluation metrics and expose the fundamental limitations arising from training sets that are too small or too noisy. A Web-based predictor, AquaSol, is available online through the ChemDB portal (cdb.ics.uci.edu) together with addnl. material.
- 21Balachandran, P. V.; Broderick, S. R.; Rajan, K. Proc. R. Soc. A, Math. Phys. Eng. Sci. 2011, 467, 2271– 229021https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFahs7vN&md5=7cccb308c7d6e8166bc81cc844b0ff0bIdentifying the 'inorganic gene' for high-temperature piezoelectric perovskites through statistical learningBalachandran, Prasanna V.; Broderick, Scott R.; Rajan, KrishnaProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (2011), 467 (2132), 2271-2290CODEN: PRSAC4 ISSN:. (Royal Society)This paper develops a statistical learning approach to identify potentially new high-temp. ferroelec. piezoelec. perovskite compds. Unlike most computational studies on crystal chem., where the starting point is some form of electronic structure calcn., we use a data-driven approach to initiate our search. This is accomplished by identifying patterns of behavior between discrete scalar descriptors assocd. with crystal and electronic structure and the reported Curie temp. (TC) of known compds.; extg. design rules that govern crit. structure-property relationships; and discovering in a quant. fashion the exact role of these materials descriptors. Our approach applies linear manifold methods for data dimensionality redn. to discover the dominant descriptors governing structure-property correlations (the 'genes') and Shannon entropy metrics coupled to recursive partitioning methods to quant. assess the specific combination of descriptors that govern the link between crystal chem. and TC (their 'sequencing'). We use this information to develop predictive models that can suggest new structure/chemistries and/or properties. In this manner, BiTmO3-PbTiO3 and BiLuO3-PbTiO3 are predicted to have a TC of 730 and 705 °C, resp. A quant. structure-property relationship model similar to those used in biol. and drug discovery not only predicts our new chemistries but also validates published reports.
- 22Kong, C. S.; Luo, W.; Arapan, S.; Villars, P.; Iwata, S.; Ahuja, R.; Rajan, K. J. Chem. Inf. Model. 2012, 52, 1812– 182022https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XptlyltL4%253D&md5=aba59dd5ad0bd37003b452d8d2de1fdaInformation-Theoretic Approach for the Discovery of Design Rules for Crystal ChemistryKong, Chang Sun; Luo, Wei; Arapan, Sergiu; Villars, Pierre; Iwata, Shuichi; Ahuja, Rajeev; Rajan, KrishnaJournal of Chemical Information and Modeling (2012), 52 (7), 1812-1820CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)For the 1st time that, using information-entropy-based methods, one can quant. explore the relative impact of a wide multidimensional array of electronic and chem. bonding parameters on the structural stability of intermetallic compds. Using an inorg. AB2 compd. database as a template data platform, the evolution of design rules for crystal chem. based on an information-theoretic partitioning classifier for a high-dimensional manifold of crystal chem. descriptors was monitored. An application of this data-mining approach to establish chem. and structural design rules for crystal chem. is demonstrated by showing that, when coupled with 1st-principles calcns., statistical inference methods can serve as a tool for significantly accelerating the prediction of unknown crystal structures.
- 23Balachandran, P. V.; Rajan, K. Acta Crystallogr. Sect. B, Struct. Sci. 2012, 68, 24– 3323https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVGnsrg%253D&md5=28c369a690b36c72230baef7da347126Structure maps for AI4AII6(BO4)6X2 apatite compounds via data miningBalachandran, Prasanna V.; Rajan, KrishnaActa Crystallographica, Section B: Structural Science (2012), 68 (1), 24-33CODEN: ASBSDK; ISSN:0108-7681. (International Union of Crystallography)This paper describes a data-driven strategy using principal component anal. and K-means clustering to discover the best classifiers for constructing structure maps. This paper describes a method to identify key crystallog. parameters that can serve as strong classifiers of crystal chemistries and hence define new structure maps. The selection of this pair of key parameters from a large set of potential classifiers is accomplished through a linear data-dimensionality redn. method. A multivariate data set of known AI4AII6(BO4)6X2 apatites was used as the basis for the study where each AI4AII6(BO4)6X2 compd. is represented as a 29-dimensional vector, where the vector components are discrete scalar descriptors of electronic and crystal structure attributes. A new structure map, defined using the two distortion angles αAII (rotation angle of AII-AII-AII triangular units) and ψAIz = 0AI-O1 (angle the AI-O1 bond makes with the c axis when z = 0 for the AI site), is shown to classify apatite crystal chemistries based on site occupancy on the A, B and X sites. The classification is accomplished using a K-means clustering anal.
- 24Srinivasan, S.; Rajan, K. Materials 2013, 6, 279– 290There is no corresponding record for this reference.
- 25Broderick, S.; Ray, U.; Srinivasan, S.; Rajan, K.; Balasubramanian, G. Appl. Phys. Lett. 2014, 104, 243110There is no corresponding record for this reference.
- 26Dey, P.; Bible, J.; Datta, S.; Broderick, S.; Jasinski, J.; Sunkara, M.; Menon, M.; Rajan, K. Comput. Mater. Sci. 2014, 83, 185– 19526https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXlvVahtg%253D%253D&md5=b41d51a3c4241f2e3bab25f4a769c88eInformatics-aided bandgap engineering for solar materialsDey, Partha; Bible, Joe; Datta, Somnath; Broderick, Scott; Jasinski, Jacek; Sunkara, Mahendra; Menon, Madhu; Rajan, KrishnaComputational Materials Science (2014), 83 (), 185-195CODEN: CMMSEM; ISSN:0927-0256. (Elsevier B.V.)This paper predicts the bandgaps of over 200 new chalcopyrite compds. for previously untested chemistries. An ensemble data mining approach involving Ordinary Least Squares (OLS), Sparse Partial Least Squares (SPLS) and Elastic Net/Least Abs. Shrinkage and Selection Operator (Lasso) regression methods coupled to Rough Set (RS) and Principal Component Anal. (PCA) methods was used to develop robust quant. structure - activity relationship (QSAR) type models for bandgap prediction. The output of the regression analyses is the predicted bandgap for new compds. based on a model using the descriptors most related to bandgap. Feature ranking algorithms were then employed to: (i) assess the connection between bandgap and the chem. descriptors used in the predictive models; and (ii) understand the cause of outliers in the predictions. This paper provides a descriptor guided selection strategy for identifying new potential chalcopyrite chemistries materials for solar cell applications.
- 27Curtarolo, S.; Setyawan, W.; Hart, G. L. W.; Jahnatek, M.; Chepulskii, R. V.; Taylor, R. H.; Wang, S.; Xue, J.; Yang, K.; Levy, O.; Mehl, M.; Stokes, H. T.; Demchenko, D. O.; Morgan, D. Comput. Mater. Sci. 2012, 58, 218– 22627https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktL8%253D&md5=8129bab53c054672274b0d6fa64172efAFLOW: An automatic framework for high-throughput materials discoveryCurtarolo, 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, DaneComputational 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.
- 28Curtarolo, S.; Setyawan, W.; Wang, S.; Xue, J.; Yang, K.; Taylor, R. H.; Nelson, L. J.; Hart, G. L. W.; Sanvito, S.; Buongiorno Nardelli, M.; Mingo, N.; Levy, O. Comput. Mater. Sci. 2012, 58, 227– 23528https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XksVyktLw%253D&md5=1fc77b7de60ced338e5f3145f3cea020AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculationsCurtarolo, Stefano; Setyawan, Wahyu; Wang, Shidong; Xue, Junkai; Yang, Kesong; Taylor, Richard H.; Nelson, Lance J.; Hart, Gus L. W.; Sanvito, Stefano; Buongiorno-Nardelli, Marco; Mingo, Natalio; Levy, OhadComputational Materials Science (2012), 58 (), 227-235CODEN: CMMSEM; ISSN:0927-0256. (Elsevier B.V.)Empirical databases of crystal structures and thermodn. properties are fundamental tools for materials research. Recent rapid proliferation of computational data on materials properties presents the possibility to complement and extend the databases where the exptl. data is lacking or difficult to obtain. Enhanced repositories that integrate both computational and empirical approaches open novel opportunities for structure discovery and optimization, including uncovering of unsuspected compds., metastable structures and correlations between various characteristics. The practical realization of these opportunities depends on a systematic compilation and classification of the generated data in addn. to an accessible interface for the materials science community. In this paper we present an extensive repository, aflowlib.org, comprising phase-diagrams, electronic structure and magnetic properties, generated by the high-throughput framework AFLOW. This continuously updated compilation currently contains over 150,000 thermodn. entries for alloys, covering the entire compn. range of more than 650 binary systems, 13,000 electronic structure analyses of inorg. compds., and 50,000 entries for novel potential magnetic and spintronics systems. The repository is available for the scientific community on the website of the materials research consortium, aflowlib.org.
- 29Kresse, G.; Furthmüller, J. Comput. Mater. Sci. 1996, 6, 1529https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmtFWgsrk%253D&md5=779b9a71bbd32904f968e39f39946190Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis setKresse, G.; Furthmuller, J.Computational Materials Science (1996), 6 (1), 15-50CODEN: CMMSEM; ISSN:0927-0256. (Elsevier)The authors present a detailed description and comparison of algorithms for performing ab-initio quantum-mech. calcns. using pseudopotentials and a plane-wave basis set. The authors will discuss: (a) partial occupancies within the framework of the linear tetrahedron method and the finite temp. d.-functional theory, (b) iterative methods for the diagonalization of the Kohn-Sham Hamiltonian and a discussion of an efficient iterative method based on the ideas of Pulay's residual minimization, which is close to an order N2atoms scaling even for relatively large systems, (c) efficient Broyden-like and Pulay-like mixing methods for the charge d. including a new special preconditioning optimized for a plane-wave basis set, (d) conjugate gradient methods for minimizing the electronic free energy with respect to all degrees of freedom simultaneously. The authors have implemented these algorithms within a powerful package called VAMP (Vienna ab-initio mol.-dynamics package). The program and the techniques have been used successfully for a large no. of different systems (liq. and amorphous semiconductors, liq. simple and transition metals, metallic and semi-conducting surfaces, phonons in simple metals, transition metals and semiconductors) and turned out to be very reliable.
- 30Blöchl, P. E. Phys. Rev. B 1994, 50, 17953– 1797930https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2sfjslSntA%253D%253D&md5=1853d67af808af2edab58beaab5d3051Projector augmented-wave methodBlochlPhysical review. B, Condensed matter (1994), 50 (24), 17953-17979 ISSN:0163-1829.There is no expanded citation for this reference.
- 31Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865– 386831https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmsVCgsbs%253D&md5=55943538406ee74f93aabdf882cd4630Generalized gradient approximation made simplePerdew, John P.; Burke, Kieron; Ernzerhof, MatthiasPhysical Review Letters (1996), 77 (18), 3865-3868CODEN: PRLTAO; ISSN:0031-9007. (American Physical Society)Generalized gradient approxns. (GGA's) for the exchange-correlation energy improve upon the local spin d. (LSD) description of atoms, mols., and solids. We present a simple derivation of a simple GGA, in which all parameters (other than those in LSD) are fundamental consts. Only general features of the detailed construction underlying the Perdew-Wang 1991 (PW91) GGA are invoked. Improvements over PW91 include an accurate description of the linear response of the uniform electron gas, correct behavior under uniform scaling, and a smoother potential.
- 32Taylor, R. H.; Rose, F.; Toher, C.; Levy, O.; Yang, K.; Buongiorno Nardelli, M.; Curtarolo, S. Comput. Mater. Sci. 2014, 93, 178– 192There is no corresponding record for this reference.
- 33Poole, C. P. Handbook of Superconductivity; Academic Press: San Diego, CA, 2000.There is no corresponding record for this reference.
- 34Lide, D. R. CRC Handbook of Chemistry and Physics; Taylor & Francis: Oxford, U.K., 2004.There is no corresponding record for this reference.
- 35National Institute of Materials Science, MaterialsInformationStation. SuperCon. http://supercon.nims.go.jp/index_en.html. 2011.There is no corresponding record for this reference.
- 36Fourches, D.; Muratov, E.; Tropsha, A. J. Chem. Inf. Model. 2010, 50, 1189– 120436https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXnvVeitLk%253D&md5=4c19d67a67094bc595f5940157ff9a2dTrust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling ResearchFourches, Denis; Muratov, Eugene; Tropsha, AlexanderJournal of Chemical Information and Modeling (2010), 50 (7), 1189-1204CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)With the recent advent of high-throughput technologies for both compd. synthesis and biol. screening, there is no shortage of publicly or com. available data sets and databases that can be used for computational drug discovery applications. Rapid growth of large, publicly available databases (such as PubChem or ChemSpider contg. more than 20 million mol. records each) enabled by exptl. projects such as NIH's Mol. Libraries and Imaging Initiative provides new opportunities for the development of chemoinformatics methodologies and their application to knowledge discovery in mol. databases. A fundamental assumption of any chemoinformatics study is the correctness of the input data generated by exptl. scientists and available in various data sets. In another recent study, the authors investigated several public and com. databases to calc. their error rates: the latter were ranging from 0.1 to 3.4% depending on the database. How significant is the problem of accurate structure representation (given that the error rates in current databases may appear relatively low) since it concerns exploratory chemoinformatics and mol. modeling research. Recent investigations by a large group of collaborators from six labs. have clearly demonstrated that the type of chem. descriptors has much greater influence on the prediction performance of QSAR models than the nature of model optimization techniques.
- 37Valle, M.; Oganov, A. R. Acta Crystallogr., Sect. A 2010, 66, 507– 51737https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtVeku7rO&md5=056854820ccfe748ead520f5dc93b967Crystal fingerprint space - a novel paradigm for studying crystal-structure setsValle, Mario; Oganov, Artem R.Acta Crystallographica, Section A: Foundations of Crystallography (2010), 66 (5), 507-517CODEN: ACACEQ; ISSN:0108-7673. (International Union of Crystallography)The initial aim of the crystal fingerprint project was to solve a very specific problem: to classify and remove duplicate crystal structures from the results generated by the evolutionary crystal-structure predictor USPEX. These duplications decrease the genetic diversity of the population used by the evolutionary algorithm, potentially leading to stagnation and, after a certain time, reducing the likelihood of predicting essentially new structures. After solving the initial problem, the approach led to unexpected discoveries: unforeseen correlations, useful derived quantities and insight into the structure of the overall set of results. All of these were facilitated by the project's underlying idea: to transform the structure sets from the phys. configuration space to an abstr., high-dimensional space called the fingerprint space. Here every structure is represented as a point whose coordinates (fingerprint) are computed from the crystal structure. Then the space's distance measure, interpreted as structure 'closeness', enables grouping of structures into similarity classes. This model provides much flexibility and facilitates access to knowledge and algorithms from fields outside crystallog., e.g. pattern recognition and data mining. The current usage of the fingerprint-space model is revealing interesting properties that relate to chem. and crystallog. attributes of a structure set. For this reason, the mapping of structure sets to fingerprint space could become a new paradigm for studying crystal-structure ensembles and global chem. features of the energy landscape.
- 38Kuz’min, V. E.; Artemenko, A. G.; Muratov, E. N. J. Comp.-Aided Mol. Des. 2008, 22, 403– 42138https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXmtVSnt7Y%253D&md5=e8a6a3085289532d90423d6ee43cd5c1Hierarchical QSAR technology based on the Simplex representation of molecular structureKuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.Journal of Computer-Aided Molecular Design (2008), 22 (6-7), 403-421CODEN: JCADEQ; ISSN:0920-654X. (Springer)This article is about the hierarchical quant. structure-activity relationship technol. (HiT QSAR) based on the Simplex representation of mol. structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technol. is a sequential soln. (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of mol. structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solns. In the SiRMS approach, every mol. is represented as a system of different simplexes (tetrat. fragments with fixed compn., structure, chirality and symmetry). The level of simplex descriptors detailing increases consecutively from the 1D to 4D representation of the mol. structure. The advantages of the approach reported here are the absence of "mol. alignment" problems, consideration of different phys.-chem. properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for mol. design. The efficiency of the HiT QSAR approach is demonstrated by comparing it with the most popular modern QSAR approaches on two representative examn. sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the mol. structure description are also highlighted. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biol. expts., among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a no. of useful utilities.
- 39Muratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Nikolaeva-Glomb, L.; Galabov, A. S.; Kuz’min, V. E. Struct Chem. 2013, 24, 1665– 167939https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsV2mtbbK&md5=239c8a803bc3cc9b1005fd51f9a8abd5QSAR analysis of poliovirus inhibition by dual combinations of antiviralsMuratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Nikolaeva-Glomb, L.; Galabov, A. S.; Kuz'min, V. E.Structural Chemistry (2013), 24 (5), 1665-1679CODEN: STCHES; ISSN:1040-0400. (Springer)We have applied Hierarchical QSAR Technol. (HiT QSAR) to the prediction of antiviral effects of paired combinations of picornavirus replication inhibitors against poliovirus 1 (Mahoney) in vitro. The inhibition from all binary combinations of eight antivirals were investigated. Simplex representation of mol. structure (SiRMS) was used for the generation of mol. descriptors of both pure compds. and all dual mixt. combinations. Predictive QSAR models were obtained using the partial least squares (PLS) method. Predictive power of the developed models was validated using eightfold external cross-validation (CV, Q2ext = 0.67-0.93). Adequate models (Q2ext = 0.53-0.97) were obtained in the same way for predicting measured inhibitory concns. at other levels (i.e., IC30, IC40, IC60, IC70). The usage of predicted values of these concns. in the framework of the feature net (FN) approach led to an insignificant increase in the quality of the obtained QSAR models (Q2ext = 0.71-0.94). Developed QSAR models were analyzed and interpreted so that structural fragments and components of the combination promoting the antiviral activity were detd. (e.g., 2-(4-methoxyphenyl)-4,5-dihydrooxazole or the combination of N-hydroxybenzimidoyl and 3-methylisoxazole). Then the resulting consensus model was used to predict novel potent combinations of drugs. Combinations of enviroxime with pleconaril, WIN52084, and rupintrivir and the mixt. of rupintrivir with disoxaril were predicted to cause the most inhibition of poliovirus 1 replication. HiT QSAR proved itself as an adequate tool for QSAR anal. of mixts. and, although the method described here is suitable only for binary mixts., it can be easily extended for more complex combinations.
- 40Muratov, E. N.; Varlamova, E. V.; Artemenko, A. G.; Polishchuk, P. G.; Kuz’min, V. E. Mol. Inf. 2012, 31, 202– 22140https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xjs1ygtrw%253D&md5=734a57799a1ae99089874916bad263b0Existing and Developing Approaches for QSAR Analysis of MixturesMuratov, Eugene N.; Varlamova, Ekaterina V.; Artemenko, Anatoly G.; Polishchuk, Pavel G.; Kuz'min, Victor E.Molecular Informatics (2012), 31 (3-4), 202-221CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)This review is devoted to the crit. anal. of advantages and disadvantages of existing mixt. descriptors and their usage in various QSAR/QSPR tasks. We describe good practices for the QSAR modeling of mixts., data sources for mixts., a discussion of various mixt. descriptors and their application, recommendations about proper external validation specific for mixt. QSAR modeling, and future perspectives of this field. The biggest problem in QSAR of mixts. is the lack of reliable data about the mixts.' properties. Various mixt. descriptors are used for the modeling of different endpoints. However, these descriptors have certain disadvantages, such as applicability only to 1 : 1 binary mixts., and additive nature. The field of QSAR of mixts. is still under development, and existing efforts could be considered as a foundation for future approaches and studies. The usage of non-additive mixt. descriptors, which are sensitive to interaction effects, in combination with best practices of QSAR model development (e.g., thorough data collection and curation, rigorous external validation, etc.) will significantly improve the quality of QSAR studies of mixts.
- 41Bastian, M.; Heymann, S.; Jacomy, M. Int. Conf. Weblogs Social Media 2009, 8, 361– 362There is no corresponding record for this reference.
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- 44Aryasetiawan, F.; Gunnarsson, O. Rep. Prog. Phys. 1998, 61, 23744https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXitlWktLw%253D&md5=a0a95f38d413d7c09a71e3c637331dcaThe GW methodAryasetiawan, F.; Gunnarsson, O.Reports on Progress in Physics (1998), 61 (3), 237-312CODEN: RPPHAG; ISSN:0034-4885. (Institute of Physics Publishing)A review with many refs. Calcns. of ground-state and excited-state properties of materials have been one of the major goals of condensed matter physics. Ground-state properties of solids have been extensively investigated for several decades within the std. d. functional theory. Excited-state properties, on the other hand, were relatively unexplored in ab initio calcns. until a decade ago. The most suitable approach up to now for studying excited-state properties of extended systems is the Green function method. To calc. the Green function one requires the self-energy operator which is non-local and energy dependent. In this article we describe the GW approxn. which has turned out to be a fruitful approxn. to the self-energy. The Green function theory, numerical methods for carrying out the self-energy calcns., simplified schemes, and applications to various systems are described. Self-consistency issues and new developments beyond the GW approxn. are also discussed as well as the success and shortcomings of the GW approxn.
- 45Heyd, J.; Scuseria, G. E.; Ernzerhof, M. J. Chem. Phys. 2003, 118, 8207– 821545https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXjtlSisLw%253D&md5=05a44dc5890abc3dfa8e1ef5338a4781Hybrid functionals based on a screened Coulomb potentialHeyd, Jochen; Scuseria, Gustavo E.; Ernzerhof, MatthiasJournal of Chemical Physics (2003), 118 (18), 8207-8215CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Hybrid d. functionals are very successful in describing a wide range of mol. properties accurately. In large mols. and solids, however, calcg. the exact (Hartree-Fock) exchange is computationally expensive, esp. for systems with metallic characteristics. In the present work, we develop a new hybrid d. functional based on a screened Coulomb potential for the exchange interaction which circumvents this bottleneck. The results obtained for structural and thermodn. properties of mols. are comparable in quality to the most widely used hybrid functionals. In addn., we present results of periodic boundary condition calcns. for both semiconducting and metallic single wall carbon nanotubes. Using a screened Coulomb potential for Hartree-Fock exchange enables fast and accurate hybrid calcns., even of usually difficult metallic systems. The high accuracy of the new screened Coulomb potential hybrid, combined with its computational advantages, makes it widely applicable to large mols. and periodic systems.
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- 52Bhalla, A. S.; Guo, R.; Roy, R. Mater. Res. Innovat. 2000, 4, 3– 2652https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXitVGqtw%253D%253D&md5=9d0450b768ef026ffb4183b2d74de8ffThe perovskite structure - a review of its role in ceramic science and technologyBhalla, A. S.; Guo, Ruyan; Roy, RustumMaterials Research Innovations (2000), 4 (1), 3-26CODEN: MRINFV; ISSN:1432-8917. (Springer-Verlag)A review with 107 refs. Starting with the history of the fundamental science of the relation of structure to compn. delineated completely by Goldschmidt, we use the perovskite structure to illustrate the enormous power of crystal chem.-based intelligent synthesis in creating new materials. The perovskite structure is shown to be the single most versatile ceramic host. By appropriate changes in compn. one can modify the most significant electroceramic dielec. (BaTiO3 and its relatives) phase in industry, into metallic conductors, superconductors or the highest pressure phases in the earth. After an historical introduction of the science, detailed treatment of the applications is confined to the most recent research on novel uses in piezoelec., ferroelec. and related applications.
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- 55Hasan, M. Z.; Kane, C. L. Rev. Mod. Phys. 2010, 82, 3045– 306755https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht1Kgsg%253D%253D&md5=4dd1d199f00e448af7ec5420a23d845fColloquium: topological insulatorsHasan, M. Z.; Kane, C. L.Reviews of Modern Physics (2010), 82 (4), 3045-3067CODEN: RMPHAT; ISSN:0034-6861. (American Physical Society)A review. Topol. insulators are electronic materials that have a bulk band gap like an ordinary insulator but have protected conducting states on their edge or surface. These states are possible due to the combination of spin-orbit interactions and time-reversal symmetry. The two-dimensional (2D) topol. insulator is a quantum spin Hall insulator, which is a close cousin of the integer quantum Hall state. A three-dimensional (3D) topol. insulator supports novel spin-polarized 2D Dirac fermions on its surface. In this Colloquium the theor. foundation for topol. insulators and superconductors is reviewed and recent expts. are described in which the signatures of topol. insulators have been obsd. Transport expts. on HgTe/CdTe quantum wells are described that demonstrate the existence of the edge states predicted for the quantum spin Hall insulator. Expts. on Bi1-xSbx, Bi2Se3, Bi2Te3, and Sb2Te3 are then discussed that establish these materials as 3D topol. insulators and directly probe the topol. of their surface states. Exotic states are described that can occur at the surface of a 3D topol. insulator due to an induced energy gap. A magnetic gap leads to a novel quantum Hall state that gives rise to a topol. magnetoelec. effect. A superconducting energy gap leads to a state that supports Majorana fermions and may provide a new venue for realizing proposals for topol. quantum computation. Prospects for observing these exotic states are also discussed, as well as other potential device applications of topol. insulators.
- 56Chen, Y. L.; Analytis, J. G.; Chu, J.-H.; Liu, Z. K.; Mo, S.-K.; Qi, X.-L.; Zhang, H.-J.; Lu, D. H.; Dai, X.; Fang, Z.; Zhang, S.-C.; Fisher, I. R.; Hussain, Z.; Shen, Z.-X. Science 2009, 325, 178– 18156https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXos1Srsbc%253D&md5=5d9c228c5a47d2348f4821fa4cbb1beeExperimental realization of a three-dimensional topological insulator, Bi2Te3Chen, Y. L.; Analytis, J. G.; Chu, J.-H.; Liu, Z. K.; Mo, S.-K.; Qi, X. L.; Zhang, H. J.; Lu, D. H.; Dai, X.; Fang, Z.; Zhang, S. C.; Fisher, I. R.; Hussain, Z.; Shen, Z.-X.Science (Washington, DC, United States) (2009), 325 (5937), 178-181CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)Three-dimensional topol. insulators are a state of quantum matter with a bulk gap and odd no. of relativistic Dirac fermions on the surface. From investigating the surface state of Bi2Te3 with angle-resolved photoemission spectroscopy, the surface state consists of a single non-degenerate Dirac cone. Furthermore, with appropriate hole doping, the Fermi level can be tuned to intersect only the surface states and indicate a full energy gap for the bulk states. Bi2Te3 is a simple model system for the three-dimensional topol. insulator with a single Dirac cone on the surface. The large bulk gap of Bi2Te3 also points to promising potential for high-temp. spintronics applications.
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- 58Xu, S.-Y.; Wray, L. A.; Xia, Y.; Shankar, R.; Petersen, A.; Fedorov, A.; Lin, H.; Bansil, A.; Hor, Y. S.; Grauer, D.; Cava, R. J.; Hasan, M. Z. Condens. Matters, 2010; arXiv:1007.5111v1.There is no corresponding record for this reference.
- 59Arakane, T.; Sato, T.; Souma, S.; Kosaka, K.; Nakayama, K.; Komatsu, M.; Takahashi, T.; Ren, Z.; Segawa, K.; Ando, Y. Nat. Commun. 2012, 3, 63659https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC387otVemtA%253D%253D&md5=5f5623a5561ad4c9f328831c3ab2a7b9Tunable Dirac cone in the topological insulator Bi(2-x)Sb(x)Te(3-y)Se(y)Arakane T; Sato T; Souma S; Kosaka K; Nakayama K; Komatsu M; Takahashi T; Ren Zhi; Segawa Kouji; Ando YoichiNature communications (2012), 3 (), 636 ISSN:.The three-dimensional topological insulator is a quantum state of matter characterized by an insulating bulk state and gapless Dirac cone surface states. Device applications of topological insulators require a highly insulating bulk and tunable Dirac carriers, which has so far been difficult to achieve. Here we demonstrate that Bi(2-x)Sb(x)Te(3-y)Se(y) is a system that simultaneously satisfies both of these requirements. For a series of compositions presenting bulk-insulating transport behaviour, angle-resolved photoemission spectroscopy reveals that the chemical potential is always located in the bulk band gap, whereas the Dirac cone dispersion changes systematically so that the Dirac point moves up in energy with increasing x, leading to a sign change of the Dirac carriers at x~0.9. Such a tunable Dirac cone opens a promising pathway to the development of novel devices based on topological insulators.
- 60Zhang, H.-J.; Liu, C.-X.; Qi, X.-L.; Dai, X.; Fang, Z.; Zhang, S.-C. Nat. Phys. 2009, 5, 438– 44260https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXms1Ols7s%253D&md5=1dfb16ea46d62e4aa237197c2204329aTopological insulators in Bi2Se3, Bi2Te3 and Sb2Te3 with a single Dirac cone on the surfaceZhang, Haijun; Liu, Chao-Xing; Qi, Xiao-Liang; Dai, Xi; Fang, Zhong; Zhang, Shou-ChengNature Physics (2009), 5 (6), 438-442CODEN: NPAHAX; ISSN:1745-2473. (Nature Publishing Group)Topol. insulators are new states of quantum matter in which surface states residing in the bulk insulating gap of such systems are protected by time-reversal symmetry. The study of such states was originally inspired by the robustness to scattering of conducting edge states in quantum Hall systems. Recently, such analogies resulted in the discovery of topol. protected states in two-dimensional and three-dimensional band insulators with large spin-orbit coupling. So far, the only known three-dimensional topol. insulator is BixSb1-x, which is an alloy with complex surface states. Here, the authors present the results of 1st-principles electronic structure calcns. of the layered, stoichiometric crystals Sb2Te3, Sb2Se3, Bi2Te3 and Bi2Se3. The authors' calcns. predict that Sb2Te3, Bi2Te3 and Bi2Se3 are topol. insulators, whereas Sb2Se3 is not. These topol. insulators have robust and simple surface states consisting of a single Dirac cone at the Γ point. The authors predict that Bi2Se3 has a topol. nontrivial energy gap of 0.3 eV, which is larger than the energy scale of room temp. The authors further present a simple and unified continuum model that captures the salient topol. features of this class of materials.
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- 74Takahashi, H.; Môri, N.; Azuma, M.; Hiroi, Z.; Takano, M. Physica C 1994, 227, 395– 39874https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXls1yju7k%253D&md5=693ff9132eb7cc773187176f5e539543Effect of pressure on the Tc of hole- and electron-doped infinite-layer compounds up to 8 GPaTakahashi, H.; Mori, N.; Azuma, M.; Hiroi, Z.; Takano, M.Physica C: Superconductivity and Its Applications (Amsterdam, Netherlands) (1994), 227 (3-4), 395-8CODEN: PHYCE6; ISSN:0921-4534.The superconducting transition temp. (Tc) of hole-doped infinite-layer SrCuO2 (Tc = 91 K), (Ca0.3Sr0.7)0.95CuO2 (Tc = 110 K), and electron-doped Sr0.92Sm0.08CuO2 (Tc = 43 K) have been measured up to 8 GPa. For SrCuO2 and (Ca0.3Sr0.7)0.95CuO2, it is obsd. that Tc increases with pressure at a rate of dTc/dP = 2.1 and 0.7 K/GPa, resp., while dTc/dP is almost zero for Sr0.92Sm0.08CuO2, although these materials have the same crystal symmetry. These differences are discussed in relation to the defect structure introduced to the hole-type materials.
- 75Bednorz, J. G.; Müller, K. A. Z. Physik B–Condens. Matter 1986, 64, 189– 19375https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaL28XlsVCgu74%253D&md5=00e010659e213e1cfc0dbf1f66bf0a5fPossible high Tc superconductivity in the barium-lanthanum-copper-oxygen systemBednorz, J. G.; Mueller, K. A.Zeitschrift fuer Physik B: Condensed Matter (1986), 64 (2), 189-93CODEN: ZPCMDN; ISSN:0722-3277.Metallic, O-deficient compds. in the Ba-La-Cu-O system, with compn. BaxLa5-xCu5O5(3-y) were prepd. in polycryst. form. Samples with x = 1 and 0.75, y >0, annealed below 900° under reducing conditions, consist of 3 phases, one of them a perovskite-like mixed valent Cu compd. Upon cooling, the samples show a linear decrease in resistivity, then an approx. logarithmic increase, interpreted as a beginning of localization. Finally, an abrupt decrease by up to 3 orders of magnitude occurs, reminiscent of the onset of percolative supercond. The highest onset temp. was obsd. in the 30 K range. It is markedly reduced by high current densities. Thus, it results partially from the percolative nature, but possibly also from 2-dimensional superconducting fluctuations of double perovskite layers of one of the phases present.
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- 87Muratov, E. N.; Artemenko, A. G.; Varlamova, E. V.; Polischuk, P. G.; Lozitsky, V. P.; Fedchuk, A. S.; Lozitska, R. L.; Gridina, T. L.; Koroleva, L. S.; Sil'nikov, V. N. Future Med. Chem. 2010, 2, 1205– 122687https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXptFWqsb8%253D&md5=f7cad474db0dd01abab9358fc6f4fa0cPer aspera ad astra: Application of Simplex QSAR approach in antiviral researchMuratov, Eugene N.; Artemenko, Anatoly G.; Varlamova, Ekaterina V.; Polischuk, Pavel G.; Lozitsky, Victor P.; Fedchuk, Alla S.; Lozitska, Regina L.; Gridina, Tatyana L.; Koroleva, Ludmila S.; Silnikov, Vladimir N.; Galabov, Angel S.; Makarov, Vadim A.; Riabova, Olga B.; Wutzler, Peter; Schmidtke, Michaela; Kuzmin, Victor E.Future Medicinal Chemistry (2010), 2 (7), 1205-1226CODEN: FMCUA7; ISSN:1756-8919. (Future Science Ltd.)A review. This review explores the application of the Simplex representation of mol. structure (SiRMS) QSAR approach in antiviral research. We provide an introduction to and description of SiRMS, its application in antiviral research and future directions of development of the Simplex approach and the whole QSAR field. In the Simplex approach every mol. is represented as a system of different simplexes (tetrat. fragments with fixed compn., structure, chirality and symmetry). The main advantages of SiRMS are consideration of the different phys.-chem. properties of atoms, high adequacy and good interpretability of models obtained and clear procedures for mol. design. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic and biol. expts. The SiRMS approach is realized as the complex of the computer program 'HiT QSAR', which is available on request.
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