Olefins production plants are large-scale plants, in most of which gaseous and liquid hydrocarbons are cracked to produce light olefins. The complex and large-scale nature of these plants makes it an utmost necessity to design and operate them with the use of computer-aided optimization and control methods. This review paper provides an overview of the reported research works on the optimization and control of different parts of olefin plants. The main research studies are discussed in two main sections: Optimal Design and Process Operation and Control. In the Optimal Design section, the state of the optimal design of cracking furnace systems, cold-end separation systems, and separation columns have been studied. Then in the Process Operation and Control section, the control of cracking furnaces, the control of cold-end separation systems, real-time optimization of olefin plants, cyclic scheduling of cracking furnace systems, production planning of olefin plants, and finally, start-up and shutdown operations in these plants have been extensively reviewed. This paper is a continuation of the three review articles published previously entitled Thermal and Catalytic Cracking of Hydrocarbons for the Production of Light Olefins, the last of which focused on process modeling and simulation.

The cold start wetting effect on Cu-SSZ-13 has been simulated via soaking catalysts with various Si/Al ratios in ammonium water at disparate pH levels. It is found that a mild treatment (pH = 9) has little effect on the selective catalytic reduction of NO_x with NH₃ performance of Cu-SSZ-13. However, on increasing the pH to 12, the deNO_x activity and resistant ability to hydrothermal aging decrease obviously. Such a decrease could be attributed to the desilication phenomenon during the soaking process, which results in a number of effects including extraction of Cu²⁺ ions from the exchange sites, decrease in acidity, and damage to the zeolite structure. Meanwhile, the alkaline treatment exhibits distinct impacts on the physicochemical properties of Cu-SSZ-13 with different Si/Al ratios. The low Si/Al ratio catalyst (Si/Al-6) is insusceptible to desilication because of a higher content of the AlO₄^– structure and extra-framework Al (Al_ef), which could hamper the desilication.

To meet the demand for high energy and long life of electric vehicles, lithium-ion batteries using Ni–Co–Mn ternary materials as cathode have become the focus of industrialization. To design a safe, reliable, and durable battery system is a necessary condition to ensure the healthy development of the new energy electric vehicle industry. The swelling force caused by the lithium-ion insertion/extraction not only does harm to the safety of the battery system but also deteriorates the battery life. Moreover, the swelling force increases with the increase in the cycle. In this work, the difference in the swelling force of batteries design with different number of electrode sheets was studied. When the gap between the electrode and the aluminum shell is the same, the number of electrode sheets in the battery is higher, the swelling force is greater, and the capacity fading is faster; the swelling force is also stronger in the module. Because of the stronger swelling force in the module with more electrode sheets, the strength of each structural component needs to be designed stronger to ensure the module is safe and durable throughout the designed life. The results of this research could be instructive in designing a battery system.

A flow-type apparatus and predictive framework were developed for measuring and estimating dipolarity/polarizability (π*) values of binary mixtures of supercritical carbon dioxide (scCO₂)–cosolvents. The π* values of scCO₂ with methanol and ethanol cosolvents (up to 10 mol %) are reported at the temperature ranging from 40 to 80 °C and pressure ranging from 10 to 20 MPa and were found to be dependent on fluid density. The predictive framework for scCO₂–cosolvent mixtures proposed in this work was the modification by the addition of correction functions (g(ρ_CO2)) of local density enhancement into the previous predictive framework for binary liquid nonpolar–polar mixtures [ Ind. Eng. Chem. Res. 2019, 58, 18986−18996]. Four g(ρ_CO2) forms with a function of CO₂ density were evaluated by considering literature local density enhancements of pure CO₂ obtained from (i) fluorescence, (ii) Raman, (ii) UV–vis spectroscopic techniques, and (iv) molecular dynamics simulations. The framework was applied to the prediction of π* of four scCO₂–cosolvent mixtures (methanol, ethanol, 2-propanol, and 1,1,1,2-tetrafluoroethane (HFC134a)) and was found to give a reliable value with an overall relative deviation of 0.03 between the experimental and calculated data, where the fluorescence g(ρ_CO2) function provided a lower deviation than the other three functions. The application of the framework to separation processes showed that the π* values were found to explain the trends of solubility, extraction yield, and fractionation recovery. The π* values determined from the framework can be used to analyze solvent effect trends in many separation processes that required only cosolvent dipole moment, pure π* component, and CO₂ density (pressure and temperature).

In this work, compared with non-Cu₂In nanoalloy counterpart Cu-In/ZrO₂ catalysts, a Cu₁In₂Zr₄-O catalyst with the structure of Cu₂In alloy exhibited an excellent performance for CO₂ hydrogenation to CH₃OH. CO₂ conversion (12.8%) and methanol selectivity (72.8%) were outstandingly higher, which indicated that the synergetic effect existed between Cu and In over the Cu₁In₂Zr₄-O catalyst. The formation of Cu₂In alloy caused high dispersion of the active species and high surface area of the Cu₁In₂Zr₄-O catalyst, enhancing catalyst reduction performance. Strong adsorption of CO₂ caused a good conversion property of the Cu₁In₂Zr₄-O catalyst. The strong interaction between the In and Cu species formed a nanoalloy and decreased the catalyst reduction temperature, which led to the high catalytic performance for CO₂ hydrogenation. The Cu₂In alloy rather than metallic Cu was the key active site for the methanol formation.

MgO nanosheets were employed to prepare CoMo catalysts with different Co/Mo ratios (CoMo/NA-MgO) by an aqueous co-impregnation method. CoMo/NA-MgO displayed an increase in the catalytic activity for hydrodesulfurization of dibenzothiophene as the Co/Mo ratio increased in the CoMo catalysts, and it reached maximal activity at the Co/Mo ratio of 0.5. The reaction rate constant (k) and turnover frequency of CoMo/NA-MgO-0.5 (2.7 × 10^–7 mol g^–1 s^–1 and 7.9 × 10^–4 s^–1, respectively) were higher than those of conventional CoMo/γ-Al₂O₃ (2.1 × 10^–7 mol g^–1 s^–1 and 4.1 × 10^–5 s^–1). Characterization results revealed that more basic sites on NA-MgO strengthen the interaction between MoO_x and NA-MgO, leading to CoMo/NA-MgO with better MoO_x dispersion than that of CoMo/γ-Al₂O₃. In addition, an increase in Co/Mo for CoMo/NA-MgO weakened the interaction of MoO_x with NA-MgO, leading to more MoO_x species transformed into a less stacked type II CoMoS phase after sulfidation, improving direct desulfurization activity.

The preparation of highly active and stable catalysts for syngas conversion is a major challenge for Fischer–Tropsch synthesis (FTS). Herein, we report a strategy to prepare a highly dispersed Co-embedded porous carbon nanocage (CoPCN) structure derived from a core–shell metal–organic framework (MOF) ZIF-8@ZIF-67 precursor. High Co loading (over wt 30%) is achieved while maintaining an optimal dispersion and particle size of the active Co phase when a ZIF-8@ZIF-67 is pyrolyzed at 920 °C. Besides, the porous channels and hollow structures of the CoPCN strengthen the diffusion of reactants and the hydrocarbon product, enhancing the C₅₊ selectivity and CO conversion. The CoPCN shows high stability in FTS with a CO conversion of 18.3%, 80.2% selectivity for long-chain hydrocarbons (C₅₊), and 8.9% selectivity for short-chain hydrocarbons (C₂–C₄) after 100 h time on stream. Compared with other MOF-derived FTS catalysts, CoPCN-920 can achieve higher C₅₊ selectivity at a lower reaction temperature. The present work uncovers the relationship between the porous structure and catalytic performance, providing an efficient method to prepare promising materials for enhanced FTS stability, activity, and selectivity.

Particle cluster velocities, cluster sizes, and solid holdups were measured in a cold-flow downer unit using CREC-GS-Optiprobes. Runs were developed in a 0.051 m ID and a 2 m high acrylic column and a feeding section with a cyclone and an eight-nozzle ring gas injector. A fluid catalytic cracking catalyst with a mean diameter of 84.4 μm and a density of 1722 kg/m³ was used. Measurements were obtained at 0.20, 0.40, and 1.80 m axial positions from the feeding section. Experiments were performed with a superficial gas velocity of 1.0–1.6 m/s and a solid mass flux of 30–50 kg/m² s. Measurements showed particle cluster distributions, which were close to normal in the feeding section and asymmetric in the stabilized region. Significant changes were noticed when clusters evolved from the feeding section to the stabilized section: cluster slip velocity values of 0.5–0.9 m/s in the downer entrance increased to 1.1–1.4 m/s in the stabilized region.

Zn species were incorporated into hierarchical ZSM-5 zeolite (Zn-ZSM-5) via in situ hydrothermal crystallization of aluminosilicate gel containing zinc metal salts. Compared to bulk ZSM-5 zeolite, incorporating 2.3 wt % Zn increased the zeolite particle size from 1–2 to 3–5 μm and changed the morphology of the zeolite crystal from cube to cuboid. The acid density of zeolite also decreased from 1.12 to 0.37 mmol/g, as well as the ratio of the Brønsted acid site to the Lewis acid site (B/L) decreased from 1.2 to 0.3. However, the proportion of medium-strong acid sites was increased from 5.4 to 35.1%. Compared with Zn-modified ZSM-5 zeolite (Zn/ZSM-5) prepared by impregnation, Zn-ZSM-5 is characteristic of homogeneous dispersed ZnOH⁺ species with a higher proportion of medium-strong acid sites (35.1 versus 15.5%) and a lower ratio of B/L (0.3 versus 0.6). For 1-hexene hydroisomerization, Zn-ZSM-5 zeolite possessed a higher selectivity of iso-alkanes than that of Zn/ZSM-5 zeolite (51.4 versus 42.4%), as well as the selectivity of aromatics (2.3 versus 1.4%), suggesting potential application in the reduction of the olefin content in FCC gasoline.

Cu/SiO₂ catalysts are prone to deactivation in the dimethyl oxalate (DMO) hydrogenation when high content of methyl glycolate (MG) is produced at a high weight hourly space velocity (WHSV). However, few research studies have focused on the deactivation mechanism, which has become the bottleneck for improving the efficiency of the syngas-to-ethylene glycol (EG) technology. Herein, the deactivation mechanism of copper-based catalysts in the synthesis of EG was studied with MG hydrogenation as the model reaction. The stability test results proved that carrier loss in the form of tetramethoxysilane (TMOS) during the reaction could destroy the structure of the catalysts to some extent. The aggregation of copper nanoparticles (NPs) was also one of the reasons for the deactivation. However, the major factor for the deactivation of the Cu/SiO₂ catalyst was deduced to be carbon deposition. The weak acid–base sites of the catalyst led to some side reactions such as alcohol dehydration, condensation, and aromatization via the intermediate of glycolic aldehyde. Larger molecules were formed and accumulated in the pores of the catalyst, leading to the carbon deposition, which caused a rapid deactivation of the catalysts. This deactivation mechanism provides an important guide to develop a highly stable copper-based catalyst for the DMO hydrogenation to EG.

Graphite-like carbon nitride (CN) has attracted much attention because of its distinct optical and photoelectrical properties, strong stability, and wide applications for environmental restoration and renewable energy. Herein, the CN nanolayer about 7.5–17.5 nm in thickness was in situ built uniformly on the external of carbonized PDA (cPDA) spheres to form the cPDA@CN core/shell nanomaterials on account of the bioinspired adhesion. They possess the mesopore about 4.8 nm in diameter and a high specific surface area (66.6 m² g^–1). The optimal cPDA@CN sample exhibits efficient catalytic activities for the rhodamine B degradation (2.19 h^–1) and H₂ release rate (630 μmol g^–1 h^–1), which are ∼15.4 and ∼10 times of pristine CN, respectively. This research affords a dextrous and scalable way to fabricate the nanostructured photocatalyst with superior performance, which may hold great promise in practical applications.

Triboelectric nanogenerators (TENGs) with high performance and biocompatibility are of demand for the development of novel medical devices and wearable electronics. Herein, a highly porous silk aerogel-based TENG (STENG) with high output performance was developed using silk fibroins extracted from silk cocoons. The silk aerogel made of 2% silk fibroin solution showed a nanofibrillated porous structure and the highest surface area, which contributed to the high triboelectric output performance of the STENG based on it. The rough surface and highly porous structure facilitated charge generation of the aerogels. The optimized STENG achieved an open circuit voltage of 52.8 V and a short circuit current of 5.2 μA, and a maximum power density of 0.37 W/m² was reached on a 1 MΩ external resistor. The STENG possesses high stability under different operation frequencies and in long term, and it could act as a power source for small electronics. Moreover, the excellent biocompatibility of silk aerogels to human cells makes the STENG possible to be used as implantable energy harvesters. In addition, because of its high tribopositivity, silk can be used as additives to fabricate composite aerogels. With an addition of 20% silk, the power of cellulose nanofibril-based TENGs improved by 3.1 times.

This study fabricated polymer–metal hybrid (PMH) materials with ultrahigh strengths using an effective electrochemical treatment strategy and direct molding bonding. It is found that the bonding strength of the prepared PMH between the polymer and metal reached as high as 21.0 MPa. Characterizations revealed the formation of a new multinanoporous Al₂O₃ layer on an aluminum (Al) alloy after electrochemical treatment. The thickness of the Al₂O₃ layer was 6.2–15.3 μm, and nanopores with an average diameter of 7.8–14.3 nm were parallelly distributed throughout the whole Al₂O₃ layer. The formation of countless nanorivets allows large-area mechanical interlocking at the interface between the polymer and Al alloy, which is thought to be the key mechanism of achieving ultrahigh strength. At the optimal treatment voltage of 18 V, the maximum mechanical strength of the PMH material was obtained, and the corresponding number of the formed nanorivets was 5.75 × 10¹⁰ in theory. Also, the average size of the nanopores was 14.3 nm. Compared to the traditional chemical treatments, the electrochemical method is no doubt a more effective treatment.

Dispersion of large amounts of carbon fillers, such as graphene, mesocarbon microbeads, and multiwalled carbon nanotubes, in water provides a route to yield nanocomposites with superior mechanical properties and high conductivities for academic studies and practical applications. In this aspect, a self-healable polymer blend of poly(acrylic acid) (PAA) and poly(ethylene oxide) (PEO) is an excellent dispersant for carbon fillers, rendering nanocomposites with a large filler content (up to 90 wt %). As the carbon filler content increases from 10 to 90 wt %, the nanocomposites transfer from healable elastomers with a high fracture strain (up to 700%) into hard plastics with outstanding conductivities (up to 1.1 × 10⁶ S m^–1). Morphological investigations by scanning electron microscopy suggested the homogeneous dispersion of the carbon fillers in the PEO/PAA polymer blend. The experimental mechanical modulus and the conductivity of the nanocomposites as functions of the filler content can be approached by the theoretical Kolarik model and the scaling law, respectively, based on a co-continuous distribution of the carbon filler and the polymer blend. A theoretical evaluation provided in this study thereby lays the ground for future development in practical application fields.

A copper magnetite nanohybrid catalyst (Cu-Fe₃O₄/Cu/C), abundant of Schottky interfaces and structural defects, with ultrathin encapsulation of graphitic carbon, was synthesized and tested. The catalyst shows enhanced catalytic activity, far higher than the single and mixed counterparts toward ultrasonic-assisted heterogeneous Fenton degradation of rhodamine-B, exhibiting a reaction rate constant of 0.146 min^–1 much larger than that over carbon-encapsulated Cu (Cu/C, 0.010 min^–1) and over Fe₃O₄ (Fe₃O₄/C, 0.009 min^–1). Besides, the catalyst also delivers good reusability, showing less than 7% decrease of removal efficiency even after four cycles. As evidenced by the electron paramagnetic resonance spectra and high-resolution transmission electron microscopy, the Schottky interface between Cu and Fe₃O₄ endows the catalyst with a good electron donor feature and significantly boosts the formation of ·OH and ·O₂^– radicals, and the conductive encapsulation layer and the abundant structural defects accelerate charge-transfer process in Fe₃O₄, which together contribute to the impressive increase of the degradation rate.

A novel type of hybrid graphene oxide/laponite (GO/L) layered membrane is developed with stable two-dimensional (2D) nanochannels for efficient separations in aqueous environments. The electrostatic attractions are generated between the positive charges at the edges of laponite nanosheets and the oxygen-containing groups of GO nanosheets, and such electrostatic attractions between the adjacent GO and laponite nanosheets provide the hybrid GO/L layered membranes strong stability in aqueous environments. When the content of laponite nanosheets in GO/L layered membranes reaches 50 wt %, the GO/L layered membranes are stable enough to be operated in both water and ethanol solutions. Because the hydrophilicity of the hybrid GO/L layered membranes is improved to some extent by the addition of hydrophilic laponite nanosheets, the water permeability of GO-based membranes could be slightly enhanced. Furthermore, because the regularity of the 2D nanochannels of hybrid GO/L layered membranes is not affected by the hybrid regular laponite nanosheets, the separation efficiency of GO-based membranes is high. Demonstrations of efficient separations with the hybrid GO/L layered membranes with 50 wt % laponite nanosheets are carried out for separating basic fuchsine and brilliant yellow dyes from aqueous solutions, and the results show both high permeability and high rejection. The proposed membranes are highly potential for water treatments such as removal of dyes, hormones, and pesticides from aqueous solutions.

Cu-BTC is a copper paddlewheel-based metal–organic framework (MOF) with great potential in gas adsorption and heterogeneous catalysis but has restricted practical applications because of its poor water stability. In this work, we propose a strategy for one-step synthesis and in situ functionalization of isopropanol (IPA)-modified Cu-BTC (Cu-BTC-IPA) with enhanced water stability. Successful incorporation of IPA into Cu-BTC was evidenced by proton nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy spectra. The introduction of methyl groups around unsaturated Cu sites can form a methyl-shielding microenvironment, endowing Cu-BTC-IPA with the ability to maintain the topology structure after being immersed in water even for 4 days. After soaking, Cu-BTC-IPA can preserve 95% of its original Brunauer–Emmett–Teller (BET) surface areas and 90% of its initial CO₂ adsorption capacity, while Cu-BTC completely lost its crystallinity. In addition, Cu-BTC-IPA managed to preserve its main crystal structure and 83% of its initial BET surface areas after 12 h of immersion in diluted HCl solution (pH = 3). The improved hydrolysis stability mechanism of Cu-BTC-IPA was investigated using density functional theory calculations. The results suggest that the strategy of incorporating IPA into Cu-BTC is very efficient in enhancing its structure stability against water and worthy of further exploitation in improving the structure stability of other MOFs with open metal sites.

Rotating drums are widely used in the industry for mixing, milling, coating, and drying processes. In the past decades, mixing of granular materials in rotating drums has been extensively investigated, but most of the studies are based on spherical particles. Particle shape has a significant effect on the flow behavior and thus mixing performance, but studies and understanding are still limited. In this work, discrete element method is employed to study the radial mixing of ellipsoids in a rotating drum. The effects of rotation speed and aspect ratio of ellipsoids on mixing quality and rate are investigated, and the underlying mechanisms are further developed. The results show that mixing index increases rapidly over time for both spheres and ellipsoids. Particles with various shapes of ellipsoids can reach well-mixed states after sufficient revolutions. The increase in rotation speed decreases the mixing rate for both spheres and ellipsoids. Generally, ellipsoids exhibit a higher mixing rate when the rotational speed ranges between 25 and 40 rpm. At 40 rpm, as the aspect ratio of ellipsoids deviates from 1.0, the mixing rate increases significantly and achieves the maximum when the aspect ratio is 0.75 or 1.5. A further increase in particle non-sphericity incurs a decrease in mixing rate. The increase in the deviation of aspect ratio from 1.0 contributes to stronger “slipping” of particles relative to the drum wall. Compared with ellipsoids, spheres have stronger diffusive mixing and weaker convective mixing in rolling or cascading regimes.

Work and heat are the two major forms of energy consumption in the process industry. They are respectively consumed in the work exchange and heat exchange networks. Because of the tight interactions between these two networks, a growing number of researchers tend to consider them as a whole: work and heat exchange networks (WHENs). However, this is a complicated system that includes not only pressure manipulation units but also heat exchangers. To synthesize such a complicated system, we propose a two-phase strategy: targeting and design. In the targeting phase, the optimal thermodynamic paths of process streams are determined by optimizing the utility consumption and estimated capital investments. To represent possible thermodynamic paths of unclassified process streams, we propose a novel stage-wise superstructure where the utility consumption and heat exchanger area of the HEN part are estimated by an extended pinch analysis method under the assumption of vertical heat transfer. With obtained thermodynamic paths, the HEN synthesis problem in the design phase is carried out by the well-known stage-wise superstructure (SWS) model. Two literature examples are presented to illustrate the effectiveness and applicability of the proposed method. In two case studies, our approach yields WHENs with 30.7 and 28.3% lower total annual cost, respectively.

Various types of risks exist in a supply chain, and disruptions could lead to economic loss or even breakdown of a supply chain without an effective mitigation strategy. The ability to detect disruptions early can help improve the resilience of the supply chain. In this paper, the application of principal component analysis (PCA) and dynamic PCA (DPCA) in fault detection and diagnosis of a supply chain system is investigated. In order to monitor the supply chain, data such as inventory levels, market demands, and amount of products in transit are collected. PCA and DPCA are used to model the normal operating conditions (NOC). Two monitoring statistics, the Hotelling’s T² and the squared prediction error (SPE), are used to detect abnormal operation of the supply chain. The confidence limits of these two statistics are estimated from the training data based on the χ²-distributions. The contribution plots are used to identify the variables with abnormal behavior when at least one statistic exceeds its limit. Two case studies are presented—a multi-echelon supply chain for a single product that includes a manufacturing process and a gas bottling supply chain with multiple products. In order to validate the proposed method, supply chain simulation models are developed using the programming language Python 3.7, and simulated data is collected for analysis. PCA and DPCA are applied to the data using the scikit-learn machine learning library for Python. The results show that abnormal operation due to transportation delay, supply shortage, and poor manufacturing yield can be detected. The contribution plots are useful for interpreting and identifying the abnormality.

Slow feature analysis (SFA) is being adopted in the process monitoring and fault diagnosis as a new latent variable extraction and dimension reduction method. As temporally relevant dynamic features extracted by SFA, slow features (SFs) can reveal typical systematic trends. However, SFA cannot resist the influence of outliers, which can deteriorate the performance of the SFA monitoring model since SFA considers that the modeling data contain only slow features and quickly varying noise. In this study, a robust SFA (RSFA) method based on the M-estimator is proposed, based on which a robust SFA monitoring model is established. Such a method can eliminate the steady and dynamic anomalies due to outliers while obtaining a precise estimation of normalization factors. It properly detects outliers in the eigendecomposition and replaces them with suitable values. Finally, the feasibility and effectiveness of the RSFA monitoring method are demonstrated by a numerical simulation and Tennessee Eastman (TE) benchmark process.

Multiple micromixing in a controlled sequence is an essential process for complex chemical synthesis of functional nanoparticles with desired physicochemical properties. Herein, we developed a unique sequential micromixing-assisted nanoparticle synthesis platform utilizing alternating current electrothermal flow (ACET). A two-fluid micromixer comprised with pairs of staggered asymmetric electrodes was first designed and characterized by joint numerical simulations and experiments to obtain the optimized electrode configuration within a straight channel. On this basis, an extra pair of symmetric electrodes was added at the main channel entrance to form a three-fluid sequential micromixer. The middle fluid would first mix with the side fluids through the symmetric ACET microvortex pair in the upstream region and then realize the side fluid mixing by the asymmetric ACET microvortex in the downstream region. Rapid and complete mixing in a short channel was observed for a relatively high flow velocity up to 7 mm/s at an AC signal of 27.5 V and 1 MHz. Sequential micromixing was achieved by flexibly adjusting the volume of each fluid and the AC voltage within the three-fluid mixer. Both the two-fluid mixing process and the three-fluid mixing process were applied to synthesize the Co–Fe Prussian blue analogue nanoparticles. In comparison with two-fluid mixing, three-fluid sequential mixing offers nanoparticles with higher dispersion, controlled particle morphology, and more regular shapes. Therefore, the ACET flow-based sequential micromixing strategy can be an alternative for complex chemical and biochemical reactions.

Fault detection and diagnosis is a crucial approach to ensure safe and efficient operation of chemical processes. This paper reports a new fault diagnosis method that exploits dynamic process simulation and pattern matching techniques. The proposed method consists of a simulated fault database which, through pattern matching, helps narrow down the fault candidates in an efficient way. An optimization based fault reconstruction method is then developed to determine the fault pattern from the candidates and the corresponding magnitude and time of occurrence of the fault. A major advantage of this approach is that it is capable of diagnosing both single and multiple faults. We illustrate the effectiveness of the proposed method through case studies of the Tennessee Eastman benchmark process.

The bis(trifluoromethanesulfonyl)imide anion, [NTf₂]⁻, can be paired with organic cations to give hydrophobic ionic liquids (ILs) that form secondary phases with water. These ILs are often identified as green solvents and considered as replacements for traditional organic solvents in chemical processes, i.e., aqueous biphasic extractions. Here, we consider a range of hydrophobic [NTf₂]⁻ ILs as extraction phases with hypersaline brines for heavy metal remediation. Extraction experiments were complicated by the partial solubility of the hydrophobic ILs, and ion chromatography was used to quantify the anion and cation losses to the aqueous phase. Although IL leaching was lower in hypersaline brine than in water (i.e., salting-out), IL losses were significant at relatively low volume ratios (V_aq/V_IL) for short-chain and functional ILs. IL purity was also affected by cation exchange; more organic cations were lost to the aqueous phase than [NTf₂]⁻ anions. Solvent replenishment costs were extremely high due to loss to the aqueous phase and high IL prices. New separation technologies will be required if these ILs are to be used industrially; recovery is unlikely to offset the cost with current separation methodologies.

Countercurrent flow in conventional dual-flow trays results in segregation in liquid and vapor flow, reducing tray efficiency. Therefore, a new dual-flow tray with fractal geometry was experimentally investigated. Air and water were used as vapor and liquid models. Flow regime and fluid dynamics parameters such as dry (ΔP_d) and wet (ΔP_w) tray pressure drop, froth height (H), clear liquid height (h_CL), and froth porosity (ε) were evaluated. The results showed a lower and a more stable ΔP_w in the fractal tray with a smaller hole diameter compared to the conventional tray when F_s ranged from 0.59 to 1.04. Fluid dynamics parameters such as H, h_CL, and ε were similar between the fractal tray with a smaller hole diameter and the conventional tray for capacity factor (F_s) values from 0.68 to 1.04 and for all values of liquid flow rate (Q_L). Fractal geometry provided a more stable liquid and vapor flow through the alternating formation of high and low pressure microzones.

This work investigated the full design, startup, operation, and control of a Kaibel divided-wall column (KDWC) for a laboratory-scale KDWC. The KDWC is designed to separate mixtures of methanol, ethanol, n-propanol, and n-butanol on the basis of a rigorous model. Effective steady-state and dynamic operation strategies are then proposed to control the practical operation of the KDWC. The proposed startup operation strategy, including total reflux, batch rectification, and continuous rectification procedures, leads to a steady state, and the steady-state design method is verified through steady-state experiments. The dynamic control strategy including a four-temperature control loop is further proposed and shows effective and precise dynamic control performance, recovering the four products to the specified values in the presence of ±20% feed disturbances. This work provides deep insight into the realization and control of a practical KDWC and will increase the possibility of industrial achievement and optimal operation of the KDWC.

Foam-flow behavior in highly permeable porous media is still unclear. Two types of pregenerated foam using porous columns filled with fine sand and 1 mm glass beads were studied in different packs of glass beads with monodisperse bead size. Foam generated in fine sand had a sharp displacing front. However, the foam pregenerated using 1 mm glass beads had a transition zone front. We found that the transition foam-quality regime was independent of the porous medium grain size only when the bubbles are smaller than the pores. The apparent viscosity of foam was found to follow the Herschel–Bulkley model if the foam bubble sizes were smaller than the pore sizes. When the bubbles were of the same size as the pores, the foam behaved like a Newtonian fluid at low flow rates and, by increasing flow rates, exhibited shear-thinning fluid behavior. Furthermore, the apparent foam viscosity was found to increase with permeability.

Hydrate bedding is defined as the gravitational segregation of hydrate particles, leading to their accumulation at the bottom of the pipe. Previous research has shown that hydrate bedding is a physical mechanism that potentially can cause blockage formation in pipelines. The data analysis from high-pressure flow loop experiments indicated that hydrate bedding could lead to increasing pressure drop, decreasing hydrate particle transportability, and increased risk of plugging. Despite the importance, reliable quantitative models to predict the occurrence of hydrate bedding under transient agglomeration conditions are currently lacking. In this work, we propose a hydrate bedding framework that combines the modeling of particle agglomeration under dynamic conditions with a critical velocity model to predict the onset of hydrate particle bedding. By applying the population balance approach, the new framework generates a distribution of hydrate agglomerates as a function of particle concentration, mixture velocity, and physical properties of the continuous phase. The distribution of agglomerates is then divided into two parts: one part contains sizes larger than the critical size (bedding), and the second part contains sizes smaller than the critical size (suspension). With this new approach, the combined bedding-agglomeration framework predicts the onset of hydrate particle bedding with reasonable accuracy for experiments performed at a high-pressure flow loop. Potentially, this framework can be integrated in transient multiphase flow simulators to compute pressure losses and manage risks due to hydrate bedding.

This study performs a novel examination of the gas transport properties in the poly(lactic acid)/montmorillonite (PLA/MMT) interface layer by comparing the permeation parameters of dry gases and those dissolved in water. Furthermore, the relationship between the transport properties of oxygen and carbon dioxide in the gas and water phases and the crystallinity/crystal structure of the PLA/MMT composite films prepared by varying the MMT content in the PLA polymer and cooling conditions was systematically investigated. The results showed that the crystallinity of the PLA/MMT composite film increased with decreasing cooling rates, while the oxygen and carbon dioxide permeabilities increased with increasing MMT content and crystallinity. A small continuous space of size ranging from a few nanometers to a few dozen nanometers wherein the gas molecules easily diffuse around the interface might be formed between the crystalline and amorphous regions, which could not be observed by microscopic analysis. This interfacial space caused an increase in the selective permeation of carbon dioxide, which exhibits higher solubility in water, and the selective elimination of oxygen, which exhibits lower solubility in water.

The relative distribution of gas flow between the bubble phase and dense phase is a very important factor that determines the performance of a gas–solid fluidized bed reactor because the dense phase provides a better gas–solid contact than the bubble phase. The gas flow through the dense phase was initially considered to be at minimum fluidization (the so-called two-phase theory) but was found to be higher with fine Group A particles. Using even smaller particles in this study, the fluidization of Group C⁺ particles, Geldart Group C particles with nano-additives, exhibited lower bubble rise velocity, lower bubble holdup, and higher gas holdup in the dense phase, etc., signifying more gas flow through the dense phase and subsequently contributing to better gas–solid contact than other particles that have ever been tested, being Group A or B. The correction factor Y that accounts for increased dense-phase gas flow in the modified two-phase theory was also found to be not a constant but a function of the superficial gas velocity, and a correlation was then proposed to characterize the division of gas flow between the two phases for these fine Group C⁺ particles based on the experimental results. The higher dense-phase gas velocity and lower bubble-phase gas velocity could improve the gas–solid contact and reactor performance for Group C⁺ particles.

CuCl₂/TiO₂ has been regarded as a highly promising sorbent to remove elemental mercury (Hg⁰) from flue gas. The density functional theory and periodical model were used to demonstrate mercury adsorption, transformation, and desorption mechanisms over the CuCl₂/TiO₂ sorbent. The calculation results show that the chemisorption mechanism dominates Hg⁰, HgCl, and HgCl₂ adsorption processes. Hg⁰ adsorption on the CuCl₂/TiO₂ surface is exothermic by 45.51 kJ/mol. Hg⁰ is found to be adsorbed on the CuCl₂/TiO₂ surface via the strong interaction between Hg and Cu atoms. Electron accumulation and depletion play a crucial role in the strong interaction between the adsorbed Hg and CuCl₂/TiO₂ surface. The formation of HgCl₂ undergoes four elementary reaction steps: Hg⁰→Hg(ads)→HgCl(ads)→HgCl₂(ads)→HgCl₂. The energy barriers of HgCl(ads) and HgCl₂(ads) formation steps are approximately 108.08 and 22.88 kJ/mol, respectively. HgCl₂ desorption from the CuCl₂/TiO₂ surface is the rate-limiting step of the whole Hg transformation process and needs a reaction heat of 346.21 kJ/mol.