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The chemical industry makes extensive use of solvents, especially for chemical reactions and separations. When considering the large number of existing solvents and the necessity for finding new and alternative ones, systematic methods for the optimal selection and molecular design of solvents become significant for efficient and sustainable chemical manufacturing. During the past decade, a substantial number of contributions have been made in this area. This article summarizes property models for predicting solvent effects and introduces theoretical methods for solvent selection and design. Recent developments in computer-aided solvent selection/design for four selected application areas including reaction rate acceleration, carbon capture, extractive desulfurization, and homogeneous catalyst recovery are briefly reviewed. To conclude, several remaining challenges and possible future directions are discussed. [ABSTRACT FROM AUTHOR]

The chemical industry makes extensive use of solvents in both reaction and separation processes. The large number of existing and potentially new solvents calls for systematic methods for optimal solvent selection and design to reduce experimental efforts and accelerate process development in the early phase. There have been numerous contributions made towards the optimal selection and design of solvents as mass separating agents for various separation processes. In comparison, despite of the strong impact of solvents on chemical reactions by changing the reaction rate and/or shifting the chemical equilibrium, limited work on reaction solvent selection has been reported. Moreover, there is still a lack of insightful perspective article on model-based reaction solvent selection/design. In this work, we address this shortcoming by summarizing the state-of-the-art studies on reaction solvent selection/design using various computational methods, with a focus on group contribution and conductor-like screening model (COSMO)-based modeling approaches. Solvent selections for reactions integrated with up- and/or downstream process design, including the impact of catalyst and a group contribution extension to the COSMO models, are highlighted as potential future directions. [Display omitted] [ABSTRACT FROM AUTHOR]

When applying ionic liquids (ILs) for solvent-sensitive extraction systems, ILs dissolved in the raffinate may lead to severe subsequent problems or a significant reduction in product quality, and thus should be particularly concerned. To screen qualified IL solvent for such systems, a rigorous criterion considering both its solubility in the raffinate and extractive ability is established. The COSMO-RS model is used to evaluate the effect of anions and cations, and suggest potential ILs meeting the criterion. Afterwards, the solubility and extractive ability of candidate ILs are investigated by experiments to further confirm their suitability. The proposed solvent screening method is exemplified for the extractive desulfurization process. [C 4 mim][H 2 PO 4 ] is pre-selected by the screening method, and its high extractive performance is experimentally verified. [ABSTRACT FROM AUTHOR]

Solvents are widely used in chemical industries, especially in various separation processes. As traditional trial-and-error solvent selection is time-consuming and expensive, model-based methods for solvent selection/design become important for efficient and sustainable chemical manufacturing. A lot of contributions have been made in this area in the past few decades. This article first reviews the prediction methods for solvent properties, including single molecular properties and mixture properties. Then, the solution strategies of solvent design problems are summarized, including generate-and-test, deterministic optimization, and stochastic optimization methods. Next, latest progresses of computer-aided solvent-process design in separation processes including liquid–liquid extraction, extractive distillation, gas absorption, and crystallization are reviewed. Finally, several remaining challenges and possible future directions for solvent design in separation processes are pointed out. [ABSTRACT FROM AUTHOR]

Capture of CO 2 with high efficiency is essential to tackle the global warming issue that has aroused widespread attention. Herein we employed the halogen-free deep eutectic solvents (DESs) consisting of imidazole (Im) and p -toluenesulfonic acid (PTSA) to absorb CO 2. The CO 2 solubility in [3Im:PTSA], [3.5Im:PTSA], and [4Im:PTSA] is measured in the range of temperature from 303.15 to 333.15 K and pressure from 110 to 1500 kPa. Henry's constants of H x and H m and thermodynamic properties of∆ sol G , ∆ sol H , and ∆ sol S are correlated from the experimental data. The comparison between the studied DESs and the reported solvents is performed based on H m. Afterwards, the experiment-dependent Jou and Mather empirical model and fully predictive COSMO-RS model are used to calculate the CO 2 solubility, which are compared with the experimental results. Finally, the interaction energies between CO 2 and DESs, as indicated by misfit, hydrogen bond, and van der Waals energies, are calculated by COSMO-RS to illustrate the absorption mechanism. • The Imidazole-PTSA based halogen-free deep eutectic solvent are used to absorb CO 2. • The CO 2 solubility data in the DESs are experimentally measured. • The experimental data are compared with Jou and Mather model and COSMO-RS model. • The absorption mechanism is analyzed using the COSMO-RS theory. [ABSTRACT FROM AUTHOR]

• The functional solvent system acts as an integrated reactor and separator. • The computer-aided solvent selection efficiently reduces the experimental work. • The aldol product is automatically purified in both batch and flow processes. • The aldehyde reactant and the reaction solvent can be recycled after the reaction. • A microflow process is developed using the new reaction/separation approach. An integrated reaction-separation process based on only solvents is presented, and thus without the need for related technical equipment (reactor-separator). Both product purification and reactant recovery are achieved automatically for an asymmetric aldol reaction employing a biphasic solvent system as compartmentalizing soft matter. Firstly, COSMO-RS based simulation is introduced as a theoretical guidance in the solvent selection for the reactant 3-chlorobenzaldehyde and non-solvent selection for the R-aldol product, (R)-4-(3-chlorophenyl)-4-hydroxybutan-2-one. This encompasses solubility as core critical parameter, as well as chemo-physical properties and environmental profiling. Such criteria-cascaded screening could effectively reduce a 7665 solvents-database into 1 candidate solvent, which is dodecane, before experimental process assessment. Secondly, this screening's top candidate was validated as the best reaction solvent by first a solubility test and then by a batch reaction, in which a conversion of 69% was achieved. As desired, the mono-phase reaction yielded spontaneously the product layer and the separate dodecane phase as the second layer, which indeed allowed facile separation of the product from the residual reactant. In a third step, a segmented flow process was developed giving a highest product yield of 63% and a total conversion 92% respectively after a 2 h residence time. [ABSTRACT FROM AUTHOR]

• Reactive extraction for different long chain ester synthesis is explored by tuning DES. • Halogen-free Brønsted acidic DESs triazole-BSA/PTSA are for the first time prepared. • Triazole-BSA/PTSA DESs are tunable from weak acid to strong acid. • σ -Potential gives consistent prediction on phase splitting with experiment. • Optimal DES for longer ester is less polar from the perspective of ester phase purity. The synthesis of long-chain esters in reactive extraction using bifunctional deep eutectic solvent (DES) demands a wide solvent selection range and optimal solvent choice. In this work, a general approach towards rational DES selection is presented. First, novel halogen-free DESs based on triazole and p -toluenesulfonic acid (PTSA) or benzenesulfonic acid (BSA) are prepared to expand the selection range of Brønsted acidic DESs, whose binary solid–liquid phase diagrams are measured to confirm the DES formation. Then, the triazole-PTSA/BSA DESs together with the imidazole (Im)-PTSA/BSA DESs are characterized by pH measurement, 1H-NMR characterization, and COSMO-RS interaction energy analysis, which reflect a two-step formation mechanism. The Im-PTSA/BSA DESs are acid-base tunable while the triazole-PTSA/BSA DESs are tunable from weak acid to strong acid. Afterwards, four strong acidic DESs at the eutectic compositions namely [Im:2BSA], [Im:2PTSA], [triazole:4BSA] and [triazole:4PTSA] are determined as dual solvent-catalyst for the intensified esterification with ester carbon chain length changing from C6 to C11. Combining σ -potential thermodynamic analysis with experimental results, the applicable boundary and change rule of carbon chain length versus different DESs are clarified. On this basis, a rational DES selection strategy is formulated aiming to the development of reactive extraction for synthesizing different long-chain esters. [ABSTRACT FROM AUTHOR]

• COSMO-RS model is applied to evaluate deterpenation performance of 77 DESs. • Influences of HBA and HBD structures on deterpenation are experimentally verified. • DESs with bromide anion have both high β 1 and S values than chloride anion. • TBAB:LEA(1:2) is selected due to its better performance than hydrous ethanol. • Liquid-liquid extraction using DES is promising for natural lemon essential oil. Lemon essential oil is a complex mixture with citral as the primary terpenoid and limonene as the main terpene. Isolation of terpene and terpenoid, known as deterpenation, is crucial for improving the essential oil quality. In this work, liquid–liquid extraction with deep eutectic solvents (DESs) is utilized for lemon essential oil deterpenation. The performance of 77 DESs formed by seven hydrogen bond acceptors (HBA) with eleven hydrogen bond donors (HBD) is evaluated using COSMO-RS model and verified experimentally. The influences of HBA and HBD structures are investigated and explained by σ-profile. Among 77 DESs, the DES composed of tetrabutylammonium bromide and levulinic acid, namely TBAB:LEA(1:2), is finally selected due to its better performance than the conventional solvent hydrous ethanol. The excellent performance of TBAB:LEA(1:2) in deterpenation of natural lemon essential oil suggests it is a promising solvent in the downstream processing of natural essential oil. [ABSTRACT FROM AUTHOR]

• Ionic liquid and deep eutectic solvent are compared as alternative CO 2 absorbent. • Multilevel screening of ionic liquid and deep eutectic solvent are performed. • Top three ionic liquids and deep eutectic solvents are screened from a large space. • CO 2 absorption experiments are performed to validate the top deep eutectic solvent. • QC calculations are performed to gain microscopic insight into CO 2 absorption. Because of the high energy consumption and volatility of organic amine solvents in conventional CO 2 capture processes, ionic liquids (ILs) and deep eutectic solvents (DESs) have been widely expected as alternative CO 2 absorbents. In this work, promising ILs and DESs are identified through a comparative, multi-level absorbent screening method proposed for the first time from a large space of cation–anion combinations and potential DES components, respectively. Important physical properties (namely melting point, viscosity, and toxicity) of potential ILs and salt components of DESs are estimated by a recently-reported deep learning model. Key thermodynamic properties including physically-based absorption and desorption potentials as well as eutectic behaviors between DES component combinations are predicted by the COSMO-RS model. Five EHS (environment, health, and safety) related properties of non-salt components of DESs are assessed by the VEGA platform. From above, the top three ILs and DESs are identified from 5,440 and 38,389 candidates, respectively. The CO 2 capture processes based on the retained ILs and DESs are simulated in Aspen Plus in rate-based mode, identifying 1-methyl-1-propylpyrrolidinium bromide: methylimidazole (1:2) as the absorbent with the highest process performance. The experiments shows that the molality-based Henry constant of CO 2 in DES is as low as 1.32, validating the competitive absorption performance of this potential DES. Finally, quantum chemistry calculations are conducted to unveil the microscopic absorption mechanism of this DES. [ABSTRACT FROM AUTHOR]

[Display omitted] • A systematic component pairing method is proposed for associative extraction. • COSMO-RS model is used to predict extraction performance and SLE. • Two exemplary separation cases validate the applicability of pairing method. • Suitable HBAs and liquid operating window are determined experimentally. • Associative extraction mechanism is unraveled by FT-IR and DFT. Associative extraction by selectively forming deep eutectic solvent (DES) with the target solute exhibits high performance toward many hard-to-separate systems; however, selecting a proper associative extractant for a specific task is challenging as high extraction efficiency and forming liquid DES should be satisfied simultaneously. In this work, a systematic component pairing method is proposed to rationally select suitable hydrogen bond acceptors (HBA) for associative extraction, which includes three steps: collecting HBA candidates, theoretical pairing from extraction potential evaluation and solid–liquid phase behavior estimation, and experimental validation. For two exemplary separation cases, (i.e., detergent range alcohol-alkane mixture and phenol-toluene mixture), suitable HBAs with high extraction performance and wide liquid operating window are successfully selected, demonstrating the reliability of the method. Hydrogen bonding interaction drives the selective formation of DES with the target solute, and the interaction strength depends on the solute structure, which in turn determines the selection of suitable HBAs. [ABSTRACT FROM AUTHOR]

[Display omitted] • SLE fitting with regular solution theory (RST) is evaluated with a large dataset. • A hybrid descriptor selection method is proposed with rigorous cross-validation. • A QSAR between RST interaction parameter and molecular descriptors is established. • 186 novel ES systems containing 99 room temperature ones are designed. Although eutectic solvents (ES), also widely termed as deep eutectic solvents (DES), have attracted significant interest in various chemical processes, the rational design of them remains challenging due to the difficulty in estimating eutectic formation. In this work, the regular solution theory (RST) and quantitative structure–activity relationship (QSAR) modelling are linked to the design of ES. The RST method meriting simplicity and solid physical basis is systematically examined for correlating the solid–liquid equilibria of 99 ES systems collected from literature. The QSAR model between the RST interaction parameters of these ES systems and the molecular descriptors of their constitutive components is developed through elaborate descriptor selection. With the final QSAR model based on 14 molecular descriptors, the eutectic temperature (T e) and composition (x e) of ES systems can be accurately predicted with mean absolute deviations of 13.89 K and 0.0973, respectively. The eutectic formation of novel component combinations can be readily predicted, thereby allowing novel ES design. As an example, from the combinations of all involved components in the collected database, 186 novel ES systems are identified and 99 of them are estimated to present as liquid under room temperature. [ABSTRACT FROM AUTHOR]