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Hydrophobic deep eutectic solvents (DESs) have been designed as effective solvents for precombustion CO2capture by using a conductor-like screening model for real solvents (COSMO-RS). Reliable CO2solubilities in various compounds and binary solvents were estimated. We have developed new DESs from 38 selected, nature-derived, hydrophobic, and CO2affinitive compounds. The possibilities of any two of these substances to form DESs were assessed from predicted activity coefficients, followed by an estimation of the CO2solubilities of the theoretically feasible DESs. 58 promising hypothetical DESs were screened out. Subsequently, eight DESs were successfully prepared and characterized. Most of these DESs have a density larger than 1.0 g/mL at 298.15 K. The DESs have a similarly low volatility as decanoic acid-menthol (1:2) and are thermally stable below 420 K. Vanillin-4-oxoisophorone (1:3) and methyl salicylate-4-oxoisophorone (1:1) have been identified to be very promising for precombustion capture, showing comparable CO2solubility and viscosity to the well-known, conventionally used Selexol solvent.

A combination of molecular modelling and experiments was conducted to study the separation of acrylic acid and propionic acid through extractive distillation with polar aprotic entrainers. It was found that acrylic acid and propionic acid can be efficiently separated through extractive distillation with a polar aprotic entrainer, resulting in the entrainment of acrylic acid and making propionic acid the most volatile compound. Vapour-liquid equilibrium experiments were conducted with 25 wt% acrylic acid, 25 wt% propionic, and 50% wt% entrainer. Dimethyl sulfoxide (DMSO) was found to induce the highest relative volatility of 1.56 at 25 mbar, which agrees well with the predicted value of 1.66 using the simulation software COSMO-RS. The difference in pKa (ΔpKa = 0.63) between acrylic acid and propionic acid is the main cause for the enhanced relative volatility. The corresponding difference in hydrogen bonding strength was calculated using COSMO-RS to result in ΔE = 1.8 kJ/mol at 25 °C between acrylic acid and propionic acid with the total mixture. When dodecane was selected as an entrainer, acrylic acid became the most volatile compound instead of propionic acid. This is explained by the fact that propionic acid has two extra hydrogen atoms available to have a Van der Waals interaction with the carbon atoms of dodecane. The difference in total Van der Waals interaction between the two carboxylic acids in the mixture with dodecane is 1.34 kJ/mol at 25 °C. This difference results in a relative volatility of 0.91, which is too small to be exploited in a distillation process, and it was concluded that for this mixture, DMSO was the best entrainer in the study.

The new predictive electrolyte model COSMO-RS-ES is evaluated and refined for the calculation of solubilities of salts in mixed solvent systems. It is demonstrated that the model is capable of predicting solid-liquid equilibria at 25 °C for ammonium and alkali metal salts quite accurately in a wide variety of solvent mixtures. Furthermore, through the introduction of Gibbs free energies of transfer of single ions it is shown that the model performance can be improved even further. This new data type also allows for an ion-specific way of evaluating the model for the first time. For some systems when calculating the solubility, larger deviations are observed, but for the vast majority of systems the model delivers good predictions. This shows that COSMO-RS-ES is a valuable tool for calculation of phase equilibria in electrolyte systems especially when the scarcity of data impede the application of models that require a higher number of parameters.

The stricter regulation regarding the use of fluorinated gases (F-gases), as a consequence of their high Global Warming Potential (GWP), represents a challenge for the refrigeration industry. The design of alternatives requires the recycling of the low to moderate GWP compounds from current refrigerant blends. However, there is not a developed and standardized technology available to recover them, and once the life cycle of the refrigeration equipment has ended, most gases are incinerated. Fluorinated ionic liquids (FILs) can effectively perform as absorbents to the complex separation of F-gas mixtures. In this work, a methodology based on the COSMO-RS thermodynamic package integrated into an Aspen Plus process simulator was used to evaluate the performance of an FIL to recover difluoromethane (R-32) from the commercial blend R-407F. The environmental sustainability of the recovery process (circular economy scenario) was analyzed with a life cycle assessment (LCA) approach, comparing the obtained results with the conventional R-32 production (benchmark scenario). The results reveal a 30% recovery of 98 wt % R-32 suitable for further reuse with environmental load reduction in the 86–99% range compared to the R-32 production. This study can guide the development of new F-gas recovery technologies to improve the environmental impacts of these compounds from a circular economy perspective., Recovery of low-GWP F-gases with ionic liquids in circular economy scenarios can achieve environmental impact reductions higher than 86%.

To develop efficient ionic liquid (IL)-based separation processes like extractive distillation, the knowledge of IL-involved vapor–liquid equilibria (VLE) is necessary. Since experimental measureme...

The application of natural antibacterial agents seems to be one of the popular research topics in the field of antibacterial materials due to their unique properties such as good biocompatibility a...

Ionic liquids (ILs) are widely used in the extraction of phenolic compounds from low-temperature coal tar (LTCT). However, both ILs and LTCT contain a certain amount of water. The existence of water may have a remarkable impact on the phenol separation performance of ILs with different structures. In this work, the capacity and selectivity for m-cresol, as well as the solubility of cumene and dodecane in different IL–H2O mixtures, were firstly calculated by the conductor-like screening model for real solvents (COSMO-RS) at infinite dilution. The calculation covers ILs with different anionic and anionic structures and different water contents. To explore the effect of water in IL on separation performance, 1-ethyl-3-methyl imidazolium acetate ([C2mim][Ac]) was selected as the representative IL, and then the molecular interactions between the [C2mim][Ac]–H2O mixture solvent and solute (including m-cresol, cumene, and dodecane) were analyzed by COSMO-RS. The results indicated that both water and m-cresol could form hydrogen bonds with [C2mim][Ac]. The competition between them leads to decreasing separation performance for m-cresol of the [C2mim][Ac]–H2O mixture with increasing water content. Moreover, through analyses of m-cresol extraction efficiency, distribution coefficient, selectivity, and entrainment of cumene and dodecane, the experimental results confirmed that the presence of water in [C2mim][Ac] had a negative effect on the separation of m-cresol. The viscosity and UV–vis spectra of the [C2mim][Ac]–H2O mixture were also measured. Water in ILs should be removed as much as possible to ensure a better dephenolization effect and avoid phenol containing wastewater.

Artemisinin is an antimalarial substance very sparingly soluble in water. In the attempt to identify environmental-friendly and non-toxic aqueous-based solvents to extract it from Artemisia annua L., the solubility of artemisinin in aqueous solutions of different hydrotropes was measured at 303.2 K, for hydrotrope concentrations up to 5 M. The ability of the studied hydrotropes for enhancing the artemisinin solubility increases in the following order: Na[N(CN)2] < Na[SCN] < [Chol][Van] < [Chol][Gal] < [N4,4,4,4]Cl < [Chol][Sal] < [P4,4,4,4]Cl < Na[Sal], with Na[Sal] allowing an increase in the solubility of 750 fold compared to pure water. The COSMO-RS model and experimental Kamlet-Taft solvatochromic parameters were applied to connect the solubility enhancement with solvent properties. At low hydrotrope concentration, the solubility increases with the decreasing of the difference between the Apolar Factors of the hydrotrope and artemisinin, while for higher hydrotrope concentration, the hydrogen-bond acceptor character of the hydrotrope seems to have an impact on the solubility enhancement. Even if some mechanistic understanding is still to unfold, quantitatively the empirical correlations of solubility enhancement with the hydrotrope concentration and the solvatochromic parameters show very high accuracy. In particular, 93% of the change on the artemisinin solubility enhancement could be explained using the hydrotrope concentration and two combined solvatochromic parameters (αβ and π∗2) as explaining variables. This work was developed within the scope of the projects CICECOAveiro Institute of Materials, UIDB/50011/2020 & UIDP/50011/2020, CIMO-Mountain Research Center, UIDB/00690/2020, and Green Health (Norte-01-0145-FEDER-000042) all financed by national funds through the FCT/MEC and when appropriate co-financed by FEDER under the PT2020 and NORTE 2020 Partnership Agreement. Isabela Sales and Silvana Mattedi thanks the finantial support from CAPES and CNPq/ Brazil (CAPES: Proc. 88881.189075/2018-01 and 88887.494428/2020- 00. CNPq: Grant 303089/2019-9 and Proc.438036/2018-2). info:eu-repo/semantics/publishedVersion

In this work, the use of plant-derived raw materials, such as terpenes, gives great strength from a sustainability perspective and enables dealing with the biocarbonate concept. Biocarbonates are produced only from CO2and residues or bio-derived compounds, describing cycloaddition reactions that couple CO2and a terpene, the latter after epoxidation, avoiding environmental charges from petroleum-derived epoxides. In this work, a comprehensive database (derived from 30 terpenes) accounting bioepoxides and corresponding biocarbonates was developed, by means of molecular simulation. Optimized structures realized by the DFT method allow using a priori tools to scan the possible applications of this new class of sustainable solvents. Using a COnductor-like Screening Model for Realistic Solvents, different biocarbonates were evaluated for their physical properties and capacity to remove value-Added or contaminant solutes from aqueous mixtures, namely, furfural, phenolic compounds, and volatile fatty acids. It was found that biocarbonates derived from terpenes generally present a higher affinity for solutes in comparison with neat terpenes. Indeed, biocarbonates allowed achieving the recovery of 99% of phenol, 98% of furfural, and 87% of acetic acid, also pointing to an advantageous scenario of higher boiling points and densities and comparable solvent losses in the aqueous phase to terpenes, The authors are grateful to Ministerio de Ciencia e Innovación of Spain (projects PID2020-118259RB-I00 and PDC2021- 120881-I00) and Comunidad de Madrid (project P2018/ EMT4348) for financial support and Centro de Computación Científica de la Universidad Autónoma de Madrid for computational facilities. E.H. thanks Spanish Ministerio de Universidades for awarding an FPU grant FPU20/03198. R.S. thanks Ministerio Universidades for his Margarita Salas contract (CA1/RSUE/2021-00585)

The availability of property data is one of the major bottlenecks in the development of chemical processes and products, often requiring time-consuming and expensive experiments or limiting the chemical space to a small number of known molecules. This bottleneck has been the motivation behind the continuing development of predictive property models. For the property prediction of novel molecules, group contribution methods have been groundbreaking. In recent times, machine learning has joined the more established property prediction models. However, even with recent successes, the integration of physical constraints into machine learning models remains challenging. Physical constraints are vital to many thermodynamic properties, such as the Gibbs-Dunham relation, introducing an additional layer of complexity into the prediction. Here, we introduce SPT-NRTL, a natural language processing model to predict thermodynamically consistent activity coefficients and provide NRTL parameters for easy use in process simulations.SPT-NRTL can be classed as an advanced group contribution model that uses characters of the SMILES code as atom groups and then dynamically constructs higher-order groups. The results show that SPT-NRTL achieves higher accuracy than UNIFAC in the prediction of activity coefficients across all functional groups and is able to predict many vapor–liquid-equilibria with near experimental accuracy, as illustrated for multiple exemplary mixtures. To ease the application of SPT-NRTL, NRTL-parameters of 100 000 000 mixtures are calculated with SPT-NRTL and provided online., Fluid Phase Equilibria, 568, ISSN:0378-3812

Novel aqueous (aq) blends of N-methyldiethanolamine (MDEA), sulfolane (TMSO2), and 1-butyl-3-methyl-imidazolium acetate ([bmim][Ac]) with amine activator 2-methylpiperazine (2-MPZ) are analyzed through conductor-like screening model for real solvents (COSMO-RS) for possible application in the chemisorption of CO2. The molecules associated are analyzed for their ground-state energy, σ potential, and σ surface. Thermodynamic and physicochemical properties have been assessed and paralleled with the experimental data. Vapor pressure of the blended systems and pure component density and viscosity have been compared successfully with the experimental data. Important binary interaction parameters for the aqueous blends over a wide temperature, pressure, and concentration range have been estimated for NRTL, WILSON, and UNIQUAC 4 models. The COSMO-RS theory is further applied in calculating the expected CO2 solubility over a pressure range of 1.0-3.0 bar and temperature range of 303.15-323.15 K. Henry's constant and free energy of solvation to realize the physical absorption through intermolecular interaction offered by the proposed solvents. Perceptive molecular learning from the behavior of chemical constituents involved indicated that the best suitable solvent is aq (MDEA + 2-MPZ).

In this work, eight CO2-derived cyclic carbonates, namely ethylene carbonate (Eth-C), propylene carbonate (Pro-C), butylene carbonate (But-C), hexylene carbonate (Hex-C), cyclohexene carbonate (Cyc-C), styrene carbonate (Sty-C), glycerol carbonate (Gly-C) and (Chloromethyl)ethylene carbonate (Chl-C) were evaluated as solvents to mitigate residual aromatic content in liquid fuels by envisioning an efficient liquid–liquid extraction process, using benzene, thiophene and pyrrole as benchmark compounds for dearomatization, desulfurization and denitrogenation processes. After evaluating at molecular scale by COSMO-RS method (activity coefficients and excess enthalpies of aromatic-cyclic carbonate mixtures), predictions of phase equilibria of ternary systems involving n-heptane are carried out by COSMO-based/Aspen methodology for evaluating the extractive properties of studied cyclic carbonates. Then, computational findings are experimentally validated for the representative Pro-C case through multicomponent liquid–liquid equilibria. Finally, the complete separation process was simulated by COSMO-based/Aspen methodology to evaluate solvent losses in extraction and distillation units, energy consumption, and aromatic purity for process specifications aimed at enhancing gasoline purity and recovery. Main results suggest that Pro-C provides promising process performance at a very competitive solvent to feed (S/F) ratio and specific energy consumption, positioning cyclic carbonates for studied separation, The authors are grateful to Comunidad de Madrid (project P2018/ EMT4348) and Ministerio de Economía y Competitividad of Spain (project PID2020-118259RB-I00) for its financial support and Centro de Computacion ´ Científica de la Universidad Autonoma ´ de Madrid (CCC) for its computational resources. E. Hern´ andez thanks Spanish Ministerio de Universidades for awarding an FPU grant FPU20/03198. Diego Rodríguez-Llorente thanks Ministerio de Ciencia, Innovacion ´ y Universidades for awarding an FPU grant (FPU18/01536)

The presence of swelling clays, namely, montmorillonite and illite-smectite mixed layer clays alike, significantly affects well stimulation processes, such as hydraulic fracturing. In this study, t...

Developing energy-saving absorbents for carbon dioxide (CO2) is essential for improving carbon capture and storage (CCS) technologies. Recently, we have designed phase separation solvents, which ca...

BACKGROUND: tert‐Butanol (TBA) and water form an azeotrope at atmospheric pressure. Therefore, extractive distillation was adopted to separate the azeotropic mixture. As a new kind of solvent, the ionic liquids (ILs) 1,3‐dimethylimidazolium dimethylphosphate ([MMIM][DMP]) and 1‐ethyl‐3‐methylimidazolium diethylphosphate ([EMIM][DEP]) were chosen to break the azeotropic point in extractive distillation. RESULTS: For the ternary mixture of TBA + water + ILs, the isobaric vapor–liquid equilibrium data at atmospheric pressure for three IL mole fractions (0.1, 0.2 and 0.3) were measured. The results indicated that the volatility of TBA relative to water became higher after [MMIM][DMP] or [EMIM][DEP] was added. The nonrandom two‐liquid (NRTL) model and the COSMO‐RS theory were used to predict the ternary experimental data. The predicted results from the NRTL model showed good agreement with the experimental data. The predicted results from COSMO‐RS showed that the vapor‐phase mole fraction basically agreed with the experimental data and the equilibrium temperatures were lower than the experimental data. σ‐Profiles, σ‐potentials and σ‐surfaces were calculated based on COSMO‐RS. The results were the same as for the experiments, namely the interaction between water and ILs was stronger than other interactions; the affinity of water and [MMIM][DMP] was stronger than that of water and [EMIM][DEP]. CONCLUSIONS: The separation of the binary azeotrope of TBA and water was achieved after the ILs [MMIM][DMP] or [EMIM][DEP] were added. The separation ability of [MMIM][DMP] was better than that of [EMIM][DEP]. © 2020 Society of Chemical Industry

Trial and error remain the most common method to select the right solvent for the extraction of natural products, in particular when dealing with novel, poorly studied solvents such as deep eutecti...

Although deep eutectic solvents (DESs) have attracted significant interest in various separation processes, rational methods guiding task-specific DES selection are still scarce. In this work, a sy...

Rapid discovery of a deep eutectic solvent (DES) and its increasing application in various scientific applications demands a well-defined polarity scale for the new generation of eutectic solvents....

The solvent‐dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid‐state and API‐solvent intermolecular interactions. These simulations suggested that apolar solute‐solute interactions could be disrupted by apolar solvents. In contrast, the polar solute‐solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.

Separation of aromatics from aliphatics following catalytic reforming or steam cracking processes is difficult and energy intensive, even with highly optimized extraction solvents like sulfolane. A...

Mixing of Ionic liquids (ILs) change their physicochemical properties nonlinearly. In this study, we analyzed changes in CO2 absorption abilities of ILs caused by mixing using quantum chemical theo...

The separation of desired monomers from a liquid-phase mixture of lignin depolymerization products is necessary to facilitate their upscaling and upgrading for industrial applications. One effectiv...

Supported liquid membranes (SLMs) containing novel green solvents are proposed as a sustainable alternative separation process in the recovery of biomolecules. In this work, succinic acid has been successfully extracted from model fermentation broths through a stripping phase-facilitated transport mechanism with four different green supported liquid membranes: two eutectic solvents (DL-menthol:OctA and N4444Cl:OctA), the bio-based solvent eucalyptol and the ionic liquid [C4pyrr][Tf2N]. A permeability activity-based model that takes into account for the first time solute-phase affinities has been developed using the quantum chemical COSMO-RS method; the model corrects the mass transfer driving force and allows extraction predictions beyond the concentration equilibrium. The best recovery has been achieved experimentally for the eucalyptol-based SLM (concentration factor of 1.4) using an alkaline aqueous solution (0.5 M NaOH) as the stripping phase. A countercurrent cascade extraction process design is proposed, and a graphical method to determine the stage number, interstage concentrations as well as mass transfer area requirements is presented. This new tool, the Permeability Activity-Based Linear Operation (PABLO) method, will substantially enhance the process design of SLMs technology for the biorefinery industry., This work was funded by the CONICYT PFCHA/DOCTORADO BECAS CHILE/2017 – 72180306. P. Gorgojo acknowledges the Spanish Ministry of Economy and Competitiveness and the European Social Fund through the Ramon y Cajal programme (RYC2019-027060-I/AEI/10.13039/501100011033). M. González-Miquel acknowledges Madrid Government (Comunidad de Madrid-Spain) for funding through the Multiannual Agreement with Universidad Politécnica de Madrid under the Excellence Programme for University Professors, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).

In an attempt to evaluate the separation of certain impurities that arise in some stages of the production of cyclohexanone, this work analyzed the possibility of removing five of these substances via rectification. Due to the scarcity of experimental vapor–liquid equilibrium data for most of the solutions in the effluent of the global process, prior knowledge of their behavior is required. In this work, two predictive models, UNIFAC and COSMO-RS, were used to determine a priori the possibility of obtaining, by distillation, the individual components of seven of the binaries formed by the combination of these five compounds. Since both procedures described quasi-ideal behavior for all the chosen solutions, the results are considered as an approximation, owing to the special nature of the studied systems. The results and characteristics of each system are discussed separately.

Lignocellulose is one of the most promising renewable bioresources for the production of chemicals. For sustainable and competitive biorefineries, effective valorization of all biomass fractions is crucial. However, current efforts in lignocellulose fractionation are limited by the use of either toxic or suboptimal solvents that do not always allow producing clean and homogeneous streams. Here, we present a computational screening approach that covers more than 8000 solvent candidates for the processing of lignocellulosic biomass. The automated screening identified highly effective, non-intuitive solvents based on physico-chemical properties, solubilities of the biomass fractions, and environmental, health and safety properties. Solubility experiments for the lignin and cellulose fraction confirmed the applicability of the proposed framework in biomass processing. In addition to the traditional "lignin-first'' approaches, we identified solvents applicable for the complete dissolution of biomass. Furthermore, we elucidated particular structural patterns in solvents featuring high lignin solubility. The most promising solvents attained lignin solubilities of more than 33 wt%.

Poorly specified mixtures are common in process engineering, especially in bioprocess engineering. The properties of such mixtures of unknown composition cannot be described using conventional thermodynamic models. The NEAT method, which has recently been developed in our group, enables the calculation of activity coefficients of known target components in such poorly specified mixtures. In NEAT, the group composition of the mixture is determined by NMR spectroscopy and a thermodynamic group contribution method is used for calculating the activity coefficients. In all previous studies with NEAT, the UNIFAC group contribution method was used. In the present work, we demonstrate that NEAT can also be applied with another important method for predicting activity coefficients: COSMO-RS. COSMO-RS (OL) developed in Oldenburg together with its group contribution version GC-COSMO-RS (OL) is used here. The new version of NEAT was successfully tested. For a variety of aqueous mixtures excellent agreement of the NEAT predictions, for which only information on the target component was used, with results that were obtained using the full knowledge on the composition of the mixture was found. The results demonstrate the generic nature of the idea of NEAT and the broad applicability of the method.

Developing multicomponent crystal forms, especially cocrystals and salts, is becoming a promising pathway to improve the solubility and bioavailability of drugs. Herein, new multicomponent crystals of SHR0302, a new generation of Janus Kinase (JAK) inhibitor that suffers from poor solubility, were developed based on a cooperative approach of computational and experimental coformer screenings. Virtual screening methods, including the conductor-like screening model for realistic solvents (COSMO-RS) and molecular complementary (MC) analysis, were employed to predict the binding affinity between SHR0302 and selected coformers. The developed screening method was capable of reducing the screening database to 30 coformers from a total of 42 proposed coformers. The proof-of-concept experimental screening study was performed to demonstrate the efficiency of computational screening, wherein three new multicomponent crystalline forms were found and fully characterized by powder X-ray diffraction, thermal analysis, and IR and 1H-NMR spectroscopy. Further, the measurements of the solubility property of these new multicomponent crystal forms reveal an apparent promotion compared with the drug alone. Finally, the receiver operator characteristic (ROC) curve was used to assess the prediction performance of the COSMO-RS model. It was found that the established screening model can effectively shorten the experimental screening time and efforts.

Ionic liquids (IL) are considered viable alternative solvents for CO2 capture. Because of this and the unlimited number of possible combinations between cations and anions, it is important to devel...

Dispersion of asphaltene in crude oil using ionic liquids (ILs) is being considered as a viable solution, in extraction and transportation processes. In this work, the interplay between asphaltene and ILs has been studied systematically to understand the effect of structural variation of ILs on asphaltene solubility. The activity coefficient of the total of 1517 ILs with different combinations of cation and anion of ILs for representative asphaltene molecule (asphaltene) was estimated via COSMO-RS (Conductor-like Screening Model for Real Solvents). COSMO_RS predictions were validated using experimental data on asphaltene solubility. Among the studied ILs, asphaltene showed high solubility in imidazolium-based ILs with hydrophobic anions. The present approach paved a way forward to rationally understand the impact of structural variation of ILs on their interaction with asphaltene molecule and to design new ILs for the dispersion and stabilization of asphaltene.

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Industrial and Engineering Chemistry Research, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/abs/10.1021/acs.iecr.9b04603, There are a large number of liquid-liquid extraction processes where ionic liquids (ILs) are proposed as solvents. However, the development of purification and IL regeneration units still represents a challenge. Several effective separation trains were proposed to regenerate ILs, but extreme vacuum is needed to achieve commercial standards, which demands extra energy and extra solvent consumptions due to recycling streams. In this proposal, the use of stripping columns stands as a promising IL regeneration technology to avoid vacuum conditions and to enhance the separation of the compounds that form the extract stream, explored in the aromatic-aliphatic separation. COSMO-based/Aspen Plus methodology is applied to extensively evaluate the role of the IL nature and easily evaluate the influence of the main operating variables, namely, temperature feed, column pressure, reboiler heat, and number of stages, in the separation efficiency. A critical comparison between the current proposal and the benchmark IL regeneration process is reported, analyzing the aromatic recovery, energy duty, and operating cost. The use of two stripping columns for the IL regeneration stage evidences the potential of this new configuration, drawing a new paradigm in which mild conditions are enough to conceptually design new separation processes involving ILs, The authors are grateful to Comunidad de Madrid (project P2018/EMT4348) and Ministerio de Economía y Competitividad of Spain (project CTQ2017-89441-R) for financial support and Centro de Computación Científica de la Universidad Autónoma de Madrid (CCC) for its computational resources

Natural products can be the basis for the development of green solvents, relevant for the advancement of new, more sustainable processes and products. In this work, 10 binary mixtures constituted by terpenes are prepared and characterized. Their solid−liquid phase diagrams show that room-temperature solvents can be prepared from solid terpenes in a wide composition range. These diagrams are accurately described by the conductor-like screening model for real solvents, showing it to be a useful predictive tool for the design of novel natural solvents. At the eutectic point, these mixtures possess low viscosities, densities lower than water, and high boiling temperatures. The low water solubility in the eutectic solvents together with its negligible impact on the properties measured is a strong indicator of the hydrophobic character of these mixtures. The tunable character of these mixtures is demonstrated by studying the solvatochromic parameters in the entire concentration region, the properties of the final solvents being tuned by simply varying the mole fraction of the terpenes. The high potential of this tunable character is shown in the selective extraction of dyes from their aqueous solutions. This work is expected to devise new insights concerning these solvents as well as to boost their application in green industrial processes. This work was developed in the scope of the project CICECO-Aveiro Institute of Materials POCI-01-0145-FEDER-007679 (UID/CTM/50011/2019) and Associate Laboratory LSRE-LCM (UID/EQU/50020/2019), funded by national funds through FCT/MCTES (PIDDAC). FCT is also acknowledged for funding the project DeepBiorefinery (PTDC/AGRTEC/1191/2014). M.A.R.M. acknowledges the financial support from NORTE-01-0145-FEDER-000006 funded by NORTE2020 through PT2020 and ERDF. L.P.S. acknowledges FCT for her Ph.D. grant SFRH/BD/135976/ 2018. G.J.M. acknowledges the national funding agencies CNPq (305870/2014-9, 309780/2014-4, 140702/2017-2, 406918/2016-3, 406963/2016-9), FAPESP (2014/21252-0, 2016/08566-1), and FAEPEX/UNICAMP (0125/16). info:eu-repo/semantics/publishedVersion

The solubility of H2 in alkylic and aromatic hydrocarbons was quantum-chemical theoretically calculated through the conductor-like screening model for real solvents (COSMO-RS). The results show tha...

In this work a new method for inclusion of pressure effects in COSMO-type activity coefficient models is proposed. The extension consists in the direct combination of COSMO-SAC and lattice-fluid ideas by the inclusion of free volume in form of holes. The effort when computing pressure (given temperature, volume, and mole numbers) with the proposed model is similar to the cost for computing activity coefficients with any COSMO-type implementation. For given pressure, computational cost increases since an iterative method is needed. This concept was tested for representative substances and mixtures, ranging from light gases to molecules with up to 10 carbons. The proposed model was able to correlate experimental data of saturation pressure and saturated liquid volume of pure substances with deviations of 1.16% and 1.59%, respectively. In mixture vapor-liquid equilibria predictions, the resulting model was superior to Soave-Redlich-Kwong with Mathias-Copeman α-function and the classic van der Waals mixing rule in almost all cases tested and similar to PSRK method, from low pressures to over 100 bar. Good predictions of liquid-liquid equilibrium were also observed, performing similarly to UNIFAC-LLE, with improved responses at high temperatures and pressures.

The present study is aimed to optimized diluent type, tri-n-butyl phosphate (TBP) composition and temperature for the reactive extraction of p-nitro phenol (PNP) in two different PNP concen...

Catalysts are of paramount importance as most chemical processes would be uneconomical without suitable catalysts. Consequently, the identification of appropriate catalysts is a key step in chemical process design. However, the number of potential catalysts is usually vast. To suggest promising candidates for experimental testing, in silico catalyst design methods are highly desirable. Still, such computational methods are in their infancy. Moreover, simple performance indicators are commonly employed as design objective instead of evaluating the actual process performance enabled by considered catalysts. Here, we present the CAT-COSMO-CAMPD method for integrated in silico design of homogeneous molecular catalysts and processes. CAT-COSMO-CAMPD integrates design of molecular catalysts with process optimization, enabling a process-based evaluation of every designed candidate catalyst. Reaction kinetics of catalytic reactions are predicted by advanced quantum chemical methods. We demonstrate for a catalytic carbamate-cleavage process that CAT-COSMO-CAMPD successfully identifies catalyst molecules maximizing the predicted process performance., Computers & Chemical Engineering, 153, ISSN:0098-1354, ISSN:1873-4375

Acid gas absorption by ionic liquids (ILs) has arisen as a promising alternative technique for biogas or natural gas upgrading. In the present work, IL-based blends are evaluated for potential thermodynamic/kinetic synergistic effects on hydrogen sulfide (H2S) capture through physical and/or chemical absorption. First, a molecular simulation analysis by means of COSMO-RS was used to select IL-based blends with enhanced H2S absorbent thermodynamic properties. Physical absorption parameters of reference (KHenry) for H2S in several IL-based blends were calculated at 298 K, involving both IL mixtures and conventional industrial absorbents (tetraglyme (TGM)) with ILs at different compositions. A Henry's constant deviation parameter (ΔHKHenryH2S) was employed to analyze the nonideal effects of the mixture on H2S gas solubility in IL-based blends. In addition, the viscosities and diffusivities of the IL-based blends were estimated as key parameters controlling H2S diffusion and absorbent uptake rates. From this analysis, a sample of IL-based blends with promising thermodynamic and kinetic properties was selected for H2S physical absorption. A process simulation analysis using the COSMO-based/Aspen Plus methodology was then carried out and the selected absorbents were evaluated by modeling H2S capture in an industrial-scale commercial packed column. One IL, 1-butyl-3-methylimidazoium acetate ([Bmim][OAc]), presenting high H2S chemical absorption and a low viscous industrial solvent (TGM) were also included. The strong kinetic control of H2S capture by physical absorption indicated the limited potential performance of IL-based blends or neat ILs in industrial equipment. In contrast, the COSMO/Aspen analysis revealed that adequate formulations based on [Bmim][OAc] and TGM present enhanced H2S absorbent properties compared to the neat compounds. These computational results may be used to guide future experimental research to design new H2S absorbents, reducing the highly demanding experimental input, Financial support from Ministerio de Economía y Competitividad of Spain (project CTQ2017-89441-R) and Comunidad de Madrid (project P2018/EMT4348) is acknowledged

Bio-based organic acids constitute an important group of building block chemicals that can be produced from renewable resources, becoming a sustainable alternative to conventional petrochemical-derived commodities. However, due to the growing number of green solvents emerging as extraction media, the proper solvent selection for biomolecule separation from fermentation broths has become a key challenge in the bio-refinery industry. The overall aim of this work is to develop a roadmap to select and design green solvents for sustainable downstream processing of bio-based organic acids. To this end, a wide range of neoteric solvents (ionic liquids, eutectic solvents and bio-based solvents) were systematically evaluated for the recovery of relevant bio-organic acids through combination of experimental and COSMO-RS molecular simulation methods. Comprehensive thermodynamic analyses evaluating the organic acid partition coefficients, excess enthalpy contributions, solvent-water affinity, and process spontaneity were performed to elucidate the main mechanism driving the separation process and to provide essential guidelines for further solvent development. Based on these findings, a rational screening approach was established to identify suitable solvents for the recovery of structurally different bio-organic acids. Ultimately, this paper provides a green solvent selection guide to design sustainable separation processes of bio-based organic acids, as valuable platform chemicals transitioning towards a bio-based economy.

BACKGROUND: The selection of competent entrainer is very important for separating azeotrope systems by extractive distillation. Ionic liquids (ILs) are outstanding entrainers due to their excellent properties. However, it is time‐consuming to choose suitable ILs from the huge database of anions and cations. Herein, the selectivity and viscosity of ILs were combined as double standards to select suitable ILs for the separation of acetonitrile and ethanol mixture. RESULTS: The selectivity and viscosity of 450 ILs (25 cations and 18 anions) were predicted based on Conductor‐like Screening Model for Real Solvents (COSMO‐RS). 1‐Butyl‐3‐methylimidazolium acetate [BMIM][Ac] was selected as a potential entrainer due to its higher selectivity and lower viscosity and [BMIM][Cl] was chosen as a comparison item as ILs with [Cl]⁻ anion have separation performance next to [Ac]⁻‐based ILs. The vapor–liquid equilibrium (VLE) data of the acetonitrile + ethanol + ILs systems were determined at 101.3 kPa and correlated with the non‐random two‐liquid (NRTL) model. The result showed that the addition of the two ILs produced a salting‐out effect on acetonitrile and enhanced the relative volatility of acetonitrile to ethanol. Furthermore, [BMIM][Ac] exhibited better separation performance than [BMIM][Cl] and our previous reported ILs, which are consistent with the predicted results. The reduced density gradient (RDG) method indicated that hydrogen bonding dominated the interactions between ethanol and IL. CONCLUSION: [BMIM][Ac] is a superior entrainer for the separation of acetonitrile–ethanol azeotrope. Compared to the previously studied ILs, there is a stronger hydrogen bond between ethanol and [BMIM][Ac]. This makes ethanol ‘bundled’ and acetonitrile more volatile, resulting in the superior separation performance of [BMIM][Ac]. © 2019 Society of Chemical Industry

When selecting solvents, not only thermodynamic criteria but also environmental, health, and safety (EHS) properties should be considered. To this end, we present a fully automated solvent selectio...

Bioisoprene, which can be produced from renewable feedstocks through fermentation, is a promising alternative to petroleum-derived isoprene. However, challenges including the selection of feasible recovery techniques for bioisoprene should be addressed to achieve economic and technical competitiveness. In this work, ionic liquids (ILs) are first introduced as solvents for the recovery of bioisoprene. To describe the thermodynamic behavior, the UNIFAC-IL model is first extended to the bioisoprene systems as it combines gas–organic chemicals in IL-containing systems. Using a computer-aided IL design (CAILD) method, six out of 248 742 structurally constrained ILs are screened as optimal candidates for their further performance evaluation. Simulation results indicate that all six ILs have much better process performance than that of the alternative, isopropyl myrisate. Moreover, [N1,1,3,0][DMP] is identified as the best IL with the lowest solvent flow rate and the highest recovery ratio of isoprene. This work shows the potential of using ILs for the recovery of bioisoprene from fermentation off-gas.

Data scarcity, bias, and experimental noise are all frequently encountered problems in the application of deep learning to chemical and material science disciplines. Transfer learning has proven effective in compensating for the lack in data. The use of quantum calculations in machine learning enables the generation of a diverse dataset and ensures that learning is less affected by noise inherent to experimental databases. In this work, we propose a transfer learning approach for the prediction of solvation free energies that combines fundamentals from quantum calculations with the higher accuracy of experimental measurements. The employed model architecture is based on the directed-message passing neural network for the molecular embedding of solvent and solute molecules. A significant advantage of models pre-trained on quantum calculations is demonstrated for small experimental datasets and for out-of-sample predictions. The improved out-of-sample performance is shown for new solvents, for new solute elements, and for the extension to higher molar mass solutes. The overall performance of the pre-trained models is limited by the noise in the experimental test data, known as the aleatoric uncertainty. On a random test split, a mean absolute error of 0.21 kcal/mol is achieved. This is a significant improvement compared to the mean absolute error of the quantum calculations (0.40 kcal/mol). The error can be further reduced to 0.09 kcal/mol if the model performance is assessed on a more accurate subset of the experimental data., Comment: Submitted to Chemical Engineering Journal, 27 Nov 2020

International audience; This study aimed to evaluate the extraction efficiency of six alternative solvents compared to hexane, conventionally used, for extraction of aromas from herbs and spices. It has been performed through theoretical approach using conductor-like screening model for real solvents (COSMO-RS) as predictive method and experimental approach based on gas chromatography–mass spectrometry (GC-MS) analysis paired with multivariate statistical analysis. Differences between theory and experiments have been noticed for cyclopentyl methyl ether (CPME) that appeared a good candidate in theory but gives the lowest extraction yield (14.12 g/L). Ethyl acetate (EtOAc) exhibited the highest extraction yield (18.74 g/L) and could be the most promising solvent to substitute hexane for aromas extraction from Pistacia. lentiscus L. leaves.

As a contribution to the 9th Industrial Fluid Property Simulation Challenge on predicting interfacial tension between water and a set of non-polar oils at temperatures up to 170 °C we have used our first-principles based model, which is based on density functional theory and uses COSMO-RS implicit solvent model thermodynamics. Our calculations predict that the oil-water interfacial tension starts to drop significantly for alkanes at temperatures above ∼100 °C, and the oil-water interfacial tension drops significantly with increased temperature already above ∼25 °C for aromatic oils. In the range 110–170 °C, the interfacial tension drops almost linearly with temperature at a rate of about −0.082 mN/m/K for dodecane and −0.147 mN/m/K for toluene. Our method predicts that for any mix of dodecane and toluene, a linear interpolation of the interfacial tension with respect to the composition is a good approximation. The agreement of our predictions with the experimental data was overall satisfying, apart from a significant difference in the temperature dependence of the dodecane-water interfacial tension. We provide results derived from other experimental measurements suggesting that the large decrease measured by the challenge organizers may be erroneous.

In this study, the densities of formaldehyde (FA) + water (H2O) binary systems with formaldehyde fractions ( x F A ) of 0.05–0.27 at temperatures (T) of 293.15, 298.15, and 313.15 K were measured at 0.1 MPa, as well as those of a formaldehyde + water + methanol (MeOH) ternary system with x F A of 0.05–0.27 and x M e O H of 0.09–0.64. A thermodynamic model was combined with the conductor-like screening model for real solvents (COSMO-RS) coupled with a chemical reaction equilibrium and mass balance to describe the species distribution in the above solutions containing poly (oxymethylene) glycols ((HO(CH2O)nH, MGn n ≥ 1) and poly (oxymethylene) hemiformals (CH3O(CH2O)nH, HFn, n ≥ 1) produced by the reactions of FA with H2O and MeOH, respectively. The densities and volumes of these unknown oligomers, MGn and HFn, were computed by the COSMO-RS method and were correlated with the polymerization degree, n, and temperature, T. Furthermore, the densities of the FA + H2O and FA + H2O + MeOH solutions were calculated based on the species distribution and COSMO-RS simulations, which reproduced the experimental data well. Finally, the excess molar volumes of the FA + H2O and FA + H2O + MeOH systems were studied for the first time.

In the presented study, COSMO-RS sigma moments were utilized in a nonlinear multivariate QSPR model for the estimation of the temperature dependent surface tension of various ionic liquids in wide surface tension (15.5–65.1 mN m−1) and temperature (268–533 K) range. The developed model is supposed to be a generally applicable, robust and accurate method for the prediction of ionic liquid's surface tension. 880 data points ensure its reliability, which values were used to establish, validate and test the method. An artificial neural network was developed, optimized and used as regression model. The prediction power of the proposed model was validated with an external data set, with a squared correlation coefficient R2 = 0.97 and a mean absolute error MAE = 1 mN m−1. The estimation ability of the model was compared against widely known methods. Furthermore, the factor sensitivity analyses of the utilized molecular descriptors allowed shedding light on the intermolecular basis of ionic liquid's surface tension. Results showed that the kind of skewness of the sigma profile, the electrostatic interaction energy and the hydrogen bonding acceptor function play the most important roles in the formation of ionic liquid's surface tension.

The use of ionic liquids (ILs) in the biorefinery process has been increasing for the past few decades. In biorefinery, the separation process with respect to sugars needs to be evaluated for an efficient process design. Therefore, the present work aims to investigate the separation of sugars and ILs by means of a precipitation process using an antisolvent method. For this purpose, both theoretical and experimental studies were conducted. Initially, the conductor-like screening model for real solvents model was employed to screen the suitable antisolvents for the separation of sugars from the ILs. From the screening study, dichloromethane (DCM) and 1,2-dichloroethane were found to be the better antisolvents for the separation process. With the selected antisolvents, precipitation experiments were conducted for the mixtures involving four different sugars and three ILs at different experimental conditions. The process variables such as different antisolvents, sugars, ILs, antisolvent–IL molar ratios, and temperatures were examined in terms of their effect on sugar removal and IL recovery. DCM was found to be the most suitable antisolvent in this study with 90–99% of sugar removal and 80–98% of IL recovery. Further, molecular dynamics simulations were adopted to understand the structural properties of carbohydrates with ILs and antisolvents via interaction energies, hydrogen bonding, and coordination numbers. It was observed that the interaction energy between the sugars and IL plays a critical role in the removal of sugar. Higher the interaction energy between the sugars and IL, lower is the sugar removal.

Guggenheim proposed a theoretical expression for the combinatorial entropy of mixing of unequal sized and linear and branched molecules to improve the Flory-Huggins model. Later the combinatorial activity coefficient equation, which was derived from Guggenheim's model, was applied in the UNIQUAC, UNIFAC, and COSMOSAC models. Here we derive from Guggenheim's entropy theory a new function for the number of nearest neighbors of a compound in a multicomponent mixture for which the knowledge of the coordination number and a reference area are not needed. This new relation requires only the mole, volume and surface fraction of the compounds in the mixture. The benefit of the new relation is that both the combinatorial and the residual term in the aforementioned models can be made lattice-independent. We demonstrate that the proposed relation simplifies the Staverman-Guggenheim combinatorial model and can be applied with success to the UNIQUAC and COSMOSPACE model in the description of vapor-liquid phase equilibria and excess enthalpy. We also show that the new expression for the number of nearest neighbors should replace the relative surface area and the number of surface patches in the residual part of the UNIQUAC and the COSMOSPACE model, respectively. As a result a more rigorous version of the UNIQUAC and the COSMOSPACE model is obtained. This could serve as a better basis for predictive models like UNIFAC, COSMO-RS and COSMOSAC.

A new COSMO-RS based electrolyte model (COSMO-RS-ES) was applied to the prediction of the solubility of CO2 in aqueous MDEA solutions. For this purpose, the model was combined with the Soave-Redlich-Kwong equation of state to describe the gas phase non-ideality. First, it was shown that the model can successfully describe the phase equilibria in the CO2 + water, as well as in alkanolamine + water systems. Using a region specific interaction parameter for the amine, the accuracy of the model for the prediction of the phase equilibrium in alkanolamine + water systems was further improved. Additionally, a detailed investigation of different amine + water systems based on the calculation of the partial molar enthalpies and entropies provided valuable insights on the properties of the systems. The description of the ternary CO2 + MDEA + H2O system was successful after a readjustment of selected interaction energy equations of the model using few parameters. The model was then applied to the prediction of the species distribution as well as the prediction of the partial pressure of CO2 at low gas loading.