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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.

In the present study, the conversion performance of hydrogen sulfide (H2S) to elemental sulfur in ionic-liquid-incorporated transition metals (ILTMs) is predicted using a conductor-like screening model for realistic solvents (COSMO-RS). The predictions were made via the establishment of a correlation between the conversion performance and solubility of H2S in ionic liquids (ILs). All molecules involved were optimized at the DFT/TZVP/M06 computational level and imported on the COSMOtherm program at equimolar conditions. For validation purposes, the solubility of ILs was predicted at 1 bar pressure. Simple regression analysis was used to establish a relationship between the solubility and conversion performance of H2S. The results indicate that the solubility prediction of ILs is accurate (R2 = 93.40%) with a p-value of 0.0000000777. Additionally, the conversion performance is generally found to be dependent on the solubility value. Furthermore, 1-butyl-3-methylimidazolium chloride [bmim][Cl] was chosen as the base IL for incorporating the transition metal, owing to its solubility and selectivity to H2S. The solubility trend of ILTMs is found to follow the following order: [bmim][NiCl3] > [bmim][FeCl4] > [bmim][CoCl3] > [bmim][CuCl3]. According to the viscosity measurements of ILTMs, [bmim][NiCl3] and [bmim][FeCl4] exhibited the highest and lowest viscosity values, respectively. Therefore, [bmim][FeCl4] is a promising ILTM owing to its higher solubility and low viscosity for the application studied.

Peanut hulls (Arachis hypogaea, Leguminosae), which are a side stream of global peanut processing, are rich in bioactive flavonoids such as luteolin, eriodictyol, and 5,7-dihydroxychromone. This study aimed to isolate these flavonoid derivatives by liquid-liquid chromatography with as few steps as possible. To this end, luteolin, eriodictyol and 5,7-dihydroxychromone were isolated from peanut hulls using two different techniques, high-performance countercurrent chromatography (HPCCC) and fast-centrifugal partition chromatography (FCPC). The suitability of the biphasic solvent system composed of n-hexane/ethyl acetate/methanol/water (1.0/1.0/1.0/1.5; v/v/v/v) was determined by the Conductor like Screening Model for Real Solvents (COSMO-RS), which allowed the partition ratio KD-values of the three main flavonoids to be calculated. After a one-step HPCCC separation of ~1000 mg of an ethanolic peanut hull extract, 15 mg of luteolin and 8 mg of eriodictyol were isolated with purities over 96%. Furthermore, 3 mg of 5,7-dihydroxychromone could be isolated after purification by semi-preparative reversed-phase liquid chromatography (semi-prep. HPLC) in purity of over 99%. The compounds were identified by electrospray ionization mass spectrometry (ESI-MS) and nuclear magnetic resonance spectroscopy (NMR).

This study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly developed Python code. To evaluate the models, a novel scoring function was formulated, considering not only the accuracy but also the bias–variance tradeoff through a learning curve analysis. An ensemble approach was adopted by selecting the top-performing regression models for test and validation subsets. The obtained model accurately back-calculated the experimental data and was used to predict the solubility of BSA in 2067 potential solvents. The analysis of the entire solvent space focused on the identification of solvents with high solubility, a low environmental impact, and affordability, leading to a refined list of potential candidates that meet all three requirements. The proposed procedure has general applicability and can significantly improve the quality and speed of experimental solvent screening.

There is a lack of knowledge on comprehensive studies when dealing with ionic liquids and extraction processes. In this work, the computational COSMO-based/Aspen multiscale methodology is applied to perform a comprehensive process analysis over a wide set of 100 common ILs after properly validating against all reliable data published, in the representative field of the aromatic/aliphatic separation. The analysis describes: i) the evolution from extractive properties to extractor behavior; ii) the influence of the rigor of the model -binary (n-heptane + toluene) or multicomponent (pyrolysis gasoline) and the process description, namely extractor or complete process with recycling streams; iii) the role of the IL at commercial specifications; iv) the role of the separation train. Main results highlight: i) leading role of mass-based distribution ratio to reduce energy consumption to assess a commercial recovery; ii) selecting an IL with a minimum selectivity required within the more efficient separation train to achieve specifications at the lower energy consumption. Therefore, this work presented a clear guide to properly select the IL extractive properties at process scale and commercial specifications, together with the development of an efficient separation train, as the best approach

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.

Deep eutectic solvents (DESs) have been proposed as a viable and more sustainable solvent for CO2 capture, owing to their low volatility and tunable properties. In this work, polymer membranes were combined with hydrophobic DESs to prepare supported liquid membranes (DES-SLMs), and the potential of using SLMs for CO2/N2 separation was investigated. COSMO-RS model simulations, bond energy analysis as well as stability tests were used to select the polymeric porous support. Hydrophobic polyvinylidene fluoride (PVDF) with a nominal pore size of 0.1 μm was chosen to support three selected hydrophobic DESs. The gas permeabilities through three selected DES-SLMs were experimentally determined, where the thymol-coumarin (1:1) based SLM showed the best performance with a CO2 permeability of 175.0 Barrer and selectivity of 30.2 at room temperature. The separation capability was further improved by mixing the DES with traditional physical absorbents. In addition, the effects of water presence in the gas phase on the DES-SLM were investigated. The membrane was physically stable, but the ideal selectivity of CO2/N2 through the membrane deteriorated with time on steam. By predicting the permeabilities of CO2 and N2 through traditional organic liquid based SLMs, the prospects of developing DESs for SLM applications were demonstrated. Finally, an advanced membrane capture process for a natural gas-fired combined cycle (NGCC) power plant was studied with process simulation and economic analysis, where the SLMs are used to purify the CO2 product.

International audience; A simple approach to predict dispersive Hansen solubility parameter δD is proposed, taking advantage of the separation of energies in the COnductor-like Screening MOdel for Realistic Solvation (COSMO-RS). The “COSMOmorph”, that is, the COSMO file(s) with all surface charge densities and dielectric energy equal to zero, allows an unambiguous splitting of energies and choice of structures and removes the requirement for the experimental existence of a homomorph. Reasonable agreement between δD of COSMOmorph and published δD for 89 solvents is obtained, with a standard deviation of 1.0 MPa1/2. Note that perfect agreement is not expected due to the shortcomings of the historical method.

The separation of dimethyl carbonate (DMC) and methanol is of great significance in industry. In this study, ionic liquids (ILs) were employed as extractants for the efficient separation of methanol from DMC. Using the COSMO-RS model, the extraction performance of ILs consisting of 22 anions and 15 cations was calculated, and the results showed that the extraction performance of ILs with hydroxylamine as the cation was much better. The extraction mechanism of these functionalized ILs was analyzed by molecular interaction and the σ-profile method. The results showed that the hydrogen bonding energy dominated the interaction force between the IL and methanol, and the molecular interaction between the IL and DMC was mainly Van der Waals force. The molecular interaction changes with the type of anion and cation, which in turn affects the extraction performance of ILs. Five hydroxyl ammonium ILs were screened and synthesized for extraction experiments to verify the reliability of the COSMO-RS model. The results showed that the order of selectivity of ILs predicted by the COSMO-RS model was consistent with the experimental results, and ethanolamine acetate ([MEA][Ac]) had the best extraction performance. After four regeneration and reuse cycles, the extraction performance of [MEA][Ac] was not notably reduced, and it is expected to have industrial applications in the separation of methanol and DMC.

International audience; A predictive tool called COSMO-RS, Conductor-Like Screening Model for Real Solvents, based on quantum chemistry, dielectric continuum models, electrostatics surface interactions, and statistical thermodynamics, has been used to predict five key physicochemical properties of raw materials used in perfumery industries. The prediction of boiling point (BP), octanol-water partition coefficient (log P), vapor pressure (VP), water solubility (WS), and Henry's law constant (HLC) of fragrance molecules has been validated with a reference data set of 166 organic compounds. Knowing these properties for a fragrance molecule is essential and being able to predict them precisely can be particularly useful in the development of new molecules or in the replacement of controversial molecules regarding safety issues without compromising the overall hedonic accord. Finally, mapping the vapor pressure versus the Henry's law constant and the octanol-water partition coefficient consistently predicts the note class of the molecules useful for release comparison of captives.

Textile products are composed of various blends of synthetic or natural polymers. Elastane increases the functionality during use phase, but impedes high quality recycling. This study investigates the selective chemical dissolution of elastane from blended textile. Hansen solubility parameters and COSMO-RS were applied for solvent screening. The most recommended biobased solvents were experimentally validated with polyester, polyamide, cotton, wool and elastane for which solubility limits were determined and hence, their selectivity towards elastane dissolution. A TGA-corrected gravimetric method was developed as quantification tool and showed that tetrahydrofurfuryl alcohol and ɣ-valerolactone have comparable elastane dissolution capabilities to classical solvents (5 mg elastane/g solvent). Polyester/elastane and polyamide/elastane blends were subjected to this process as case studies. The LCA study showed that this selective solvent-based dissolution process saves 60% CO2-eq./kg textile waste compared to incineration. This interdisciplinary work can set the benchmark for further developing and upscaling physical/dissolution recycling processes for blended textiles.

Ionic liquids (ILs) have been demonstrated as promising alternatives to conventional entrainers in separation of azeotropic mixtures mostly investigating phase equilibrium and process design scenarios. However, proper selection of ILs for a specific task always remains challenging. Hence a simulation tool, i.e. conductor like screening model for real solvents (COSMO-RS) was applied to address this challenge. Furthermore, screened ILs were simulated as entrainers for ethanol water separation by extractive distillation. The current study also aims to demonstrate a systematic approach to retrofit existing processes, by employing ILs as green entrainers. Screening of twenty-five (25) ILs was carried out using COSMO-RS to select suitable ILs as green entrainers based on activity coefficient, capacity and selectivity. Results illustrated that tetramethylammonium chloride ([TMAm][Cl]) due to its strong hydrogen bonding ability was found to be the best ILs entrainer. Moreover, in order to reduce the operating costs without compromising desired product purity (ethanol purity ≥99.5% in top product), the selected ILs (8 kg/h) in a mixture with ethylene glycol (72 kg/h) were simulated using Aspen plus v.11. The simulation results revealed that by combining tetramethylammonium chloride (2 kg/h) with ethylene glycol (78 kg/h) reduced 7.26 tons of CO2 emissions/year through heat integration by saving 1.49*108 kJ/year energy besides minimizing operating costs. In conclusion, the systematic selection of ILs as green entrainers in combination with ethylene glycol and then the appropriate simulation of the whole system will ultimately reduce the cost of the separation process and reduce the emission of greenhouse gases as well utilization of toxic conventional entrainers.

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...

A preocupação crescente com o meio ambiente, nomeadamente com os gases de efeito estufa, levam muitas organizações governamentais a implementar regulamentações cada vez mais rígidas e restritivas. Entre estas regulamentações, a redução do limite de enxofre nos combustíveis para valores ultrabaixos (10 ppm) criou uma necessidade de desenvolvimento tecnológico que permita a atualização/otimização de processos industriais existentes. A busca por tecnologias inovadoras que sejam mais eficientes a nível ambiental, economicamente viáveis e que sejam capazes de alcançar estas exigências tem-se tornado um desafio. Uma nova classe de solventes, os líquidos iónicos, tem surgido no mercado. Estes apresentam propriedades excecionais, como boa estabilidade térmica e química, baixa pressão de vapor e elevada condutividade iónica o que fez com que sejam alvo de interesse da comunidade académica e industrial. De facto, estudos sobre a potencialidade dos LI como solventes em diversas separações, como a dessulfurização extrativa, têm demostrado o seu elevado potencial. Neste trabalho a possibilidade de realizar a dessulfurização da nafta usando líquidos iónicos é proposta como alternativa viável à separação pretendida. Teoricamente, é possível sintetizar cerca de 1 milhão de líquidos iónicos o que torna impossível estudá-los experimentalmente, deste modo, para selecionar os melhores líquidos iónicos para a extração de um total de 565 ppm de compostos sulfurados da nafta utilizou-se o modelo de coeficientes de atividade preditivo Condutor-like Screening Model for Real Solvents (COSMO-RS). O COSMO-RS permite obter não só o equilíbrio de fases entre o solvente e uma corrente sintética representativa da corrente da indústria, como um conjunto de informações adicionais tanto do equilíbrio de fases como dos líquidos iónicos puros. A eventual correlação entre as propriedades do solvente e o equilíbrio de fases estudado vão ser tratados com modelos de machine learning, nomeadamente k-Nearest Neighbors, Decision Tree, Random Forest, Gradient Boosting e Neural Network, de modo a encontrar e propor uma correlação que permita, para novos solventes, identificar o seu potencial como agentes de extração. The growing concern with the environment, namely greenhouse gases, led many governmental organisations to implement increasingly rigid and restrictive regulations. Among these regulations, reducing the sulphur limit in fuels to ultra-low values (10 ppm) has created a need for technological development that allows the updating/optimisation of existing industrial processes. The search for innovative technologies that are more efficient at the environmental level, economically viable and capable of meeting these requirements has become a challenge. Ionic liquids are a new type of solvent that has emerged on the market. These have exceptional properties such as good thermal and chemical stability, low vapour pressure, and high ionic conductivity, making them an object of interest to the academic and industrial community. In fact, studies on the potential of LI as solvents in various separations, such as extractive desulfurization, have demonstrated their high potential. This work proposes the possibility of performing the desulphurisation of naphtha using ionic liquids as a viable alternative to the desired separation. Theoretically, it is possible to synthesise about 1 million ionic liquids, which makes it impossible to study them experimentally. Therefore, to select the best ionic liquids for the extraction of a total of 565 ppm of sulphur compounds from naphtha, the predictive activity coefficient model Conductor-like Screening Model for Real Solvents (COSMO-RS) was used. COSMO-RS allows not only the phase equilibrium between the solvent and a synthetic stream representative of the industry stream to be obtained but also a range of additional information from both the phase equilibrium and pure ionic liquids. The possible correlation between the solvent properties and the studied phase equilibrium will be treated with machine learning models, namely k-Nearest Neighbors, Decision Tree, Random Forest, Gradient Boosting and Neural Network, in order to find and propose a correlation that allows, for new solvents, to identify their potential as extraction agents. Mestrado em Engenharia Química

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

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.

This study provides guidance on using polyurethane foam-based passive air samplers (PUF-PASs) for atmospheric nonane chlorinated paraffins (C9-CPs) and short-chain CPs (SCCPs) and reports SCCP concentrations in air in the Greater Toronto Area (GTA), Canada. We estimated the partition coefficients between PUF and air (KPUF-A) and between octanol and air (KOA) for C9-CP and SCCP congeners using the COSMO-RS method, so that PUF disk uptake profiles for each formula group could be calculated. We then measured SCCP concentrations in PUF disk samples collected from distinct source sectors in urban air across the GTA. Concentrations in samplers were used to calculate C9-CP and SCCP concentrations in air and the PUF disk uptake profiles revealed that time-weighted linear phase sampling was possible for congeners having log KOA values greater than 8.5. The highest SCCP concentrations, with an annual average concentration of 35.3 ng/m3, were measured at the industrial site, whereas lower but comparable SCCP concentrations were found in residential and background sites, with annual averages of 7.73 and 10.5 ng/m3, respectively. No consistent seasonal variation in SCCP concentrations was found in the six distinct source sectors. Direct measurements of KPUF-A and KOA values as a function of temperature could be used to increase accuracy in future studies.

The aim of this project is to improve solubility and dissolution rate of active pharmaceutical ingrednient via cocrystallization.

Hydrofluorocarbons (HFC) are fluorinated compounds used globally for refrigeration. These gases have been shown to contain a greenhouse potential of up to 22,000 times that of CO2. Thus, 1298 type-5 deep eutectic solvents (DES) were examined for the absorption and interaction mechanisms of difluoromethane (R32), due to their non-polar attributes. Of these solvents, quaternary ammonium salts mixed with various species of hydrogen bond donators (HBD) produced the most favorable interactions, with ln activity coefficients predicted to be as low as −1.39 at 1:1 compositional ratio. These DES were further studied for compositional analysis where pure tetrabutylammonium bromide showed the strongest interaction potential. The pressure study showed a linear solubility increase with a pressure increase reaching up to 86 mol/mol% in a methyltrioctylammonium bromide and polyethylene glycol mixture at 9 bar. The van der Waals interaction is the driving force of absorption with ~3x enthalpic release over hydrogen bonding. All chemicals contain strong potential for an environmentally friendly solution, as is evident through an environmental health and safety analysis.

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

As green solvents, ionic liquids (ILs) are quite suitable for the absorption of volatile organic compounds (VOCs) such as benzene and its homologues. However, solvent selection is the key to the VOC absorption process. In the present study, a rapid solvent screening tool, Conductor-like Screening Model for Real Solvents (COSMO-RS), was used to predict the solubility of toluene in 816 ILs. The effects of four structure characters, namely, the type and alkyl chain length of the cations and anions on the solubility of toluene were discussed. The following conclusions were drawn from the results: (1) ILs with pyrrolidinium-based cations showed better solubility than pyridinium- and imidazolium-based ones. (2) The solubility of toluene in PF6-based ILs increased with the increasing alkyl chain length, while its solubility in Ac-based ILs exhibited the opposite trend. (3) Toluene showed greater solubility in Cl-based ILs than those based on other anions. (4) The solubility of toluene increased with the anion alkyl chain length. Ac-based ILs were chosen as the most promising potential solvents, and further studied to determine the relationship between various interaction energy parameters and toluene solubility. The results showed that the misfit energy played a dominant role during the absorption process. Furthermore, several ILs were selected for experimental verification of the predicted solubility behavior using liquid and gaseous toluene. The results demonstrated that COSMO-RS could be used to semi-quantitatively and qualitatively predict the solubility of toluene, and this model had promising prospects in screening ILs for VOCs absorption. In summary, this study provided a fundamental basis and practical data for the control and treatment of VOCs.

2-Ethylhexyl acrylate (2-EHA) is one of the most widely used acrylates in the polymer industry, which is synthesized via Fisher esterification that is limited by chemical equilibrium. To intensify the esterification process, in this work, reactive extraction concept is proposed, with halogen-free deep eutectic solvent (DES [Im:2PTSA]) as dual solvent-catalyst that consists of imidazole (Im) and p-toluenesulfonamide (PTSA). The bifunctional effects of the DES [Im:2PTSA] are evaluated by thermodynamic analysis and experimental study. Favorable phase splitting is verified by σ-potential analysis predicted by COSMO-RS theory, combined with experiments, and the optimal acid-to-alcohol molar ratio is set to 1.2. The esterification kinetics is then experimentally determined and fitted using the molar-based and activity-based pseudo-homogeneous (PH) models, respectively. The activity-based PH model, that considers the bifunctional roles of the DES, proves to be more accurate with small RMSD of 0.0344. The stability of DES after recycling is validated to further confirm the industrial prospects of DES [Im:2PTSA] in 2-EHA production.

The CO2 solubilities (including CO2 Henry’s constant) in physical- and chemical-based ILs/DESs and the COSMO-RS models describing these properties were comprehensively collected and summarized. The summarized results indicate that chemical-based ILs/DESs are superior to physical-based ILs/DESs for CO2 capture, especially those ILs have functionalized cation and anion, and superbase DESs; some of the superbase DESs have higher CO2 solubilities than those of ILs; the best physical- and chemical-based ILs, as well as physical- and chemical-based DESs are [BMIM][BF4] (4.20 mol kg-1), [DETAH][Im] (11.91 mol kg-1), [L-Arg]-Gly 1:6 (4.92 mol kg-1) and TBD-EG 1:4 (12.90 mol kg-1), respectively. Besides the original COSMO-RS mainly providing qualitative predictions, six corrected COSMO-RS models have been proposed to improve the prediction performance based on the experimental data, but only one model is with universal parameters. The newly determined experimental results were further used to verify the perditions of original and corrected COSMO-RS models. The comparison indicates that the original COSMO-RS qualitatively predicts CO2 solubility for some but not all ILs/DESs, while the quantitative prediction is incapable at all. The original COSMO-RS is capable to predict CO2 Henry’s constant qualitatively for both physical-based ILs and DESs, and quantitative prediction is only available for DESs. For the corrected COSMO-RS models, only the model with universal parameters provides quantitative predictions for CO2 solubility in physical-based DESs, while other corrected models always show large deviations (>83%) compared with the experimental CO2 Henry’s constants. Validerad;2021;Nivå 2;2021-07-05 (beamah);Forskningsfinansiärer: K. C. Wang Education Foundation (No. GJTD-2018-04); National Natural Science Foundation of China (No. 21890764, 21838010, 21776276 & 21701024); Foundation for Distinguished Young Talents in Higher Education of Fujian Province (GY-Z17067).

A suitable ionic liquid for methyl chloride drying experiment was screened out from 210 ionic liquids by COSMO-RS model. Moreover, the experimental mechanism of ionic liquids drying is further explained by the COSMO-RS model, and it is further confirmed by analyzing the binding energy. The solubility of methyl chloride in [EMIM][BF4] and TEG and [EMIM][BF4]+H2O was completed, and the experimental results well proved the reliability of the UNIFAC-Lei model. The unknown interaction parameters were obtained through the solubility data of this work and the experimental data in the literatures. The methyl chloride drying experiment was completed in the laboratory, and the water content of the methyl chloride can be reduced to below 200 ppm. The simulation of the methyl chloride drying process using [EMIM][BF4] or TEG as absorbents was carried out by ASPEN software on an industrial scale. The final simulation results show that the [EMIM][BF4] drying process has lower energy consumption and better drying effect.

For the design of eutectic solvents (ESs, usually also known as deep eutectic solvents), the prediction of the solid–liquid equilibria (SLE) between candidate components is of primary relevance. In the present work, the SLE prediction of binary eutectic solvent systems by the COSMO-RS model is systematically evaluated, thereby examining the applicability of this method for ES design. Experimental SLE of such systems are first collected exhaustively from the literature, following which COSMO-RS SLE calculations are accordingly carried out. By comparing the experimental and predicted eutectic points (eutectic temperature and eutectic composition) of the involved systems, the effects of salt component conformer and COSMO-RS parameterization as well as the applicability for different types of components (specifically the second component paired with the first salt one) are identified. The distinct performances of COSMO-RS SLE prediction for systems involving different types of components are further interpreted from the non-ideality and fusion enthalpy point of view.

1,5-Pentanediamine (PDA) produced by biological fermentation becomes popular, but the separation of PDA from the broth is a typical difficult problem. In this work, the performance of 200 ionic liquids (ILs), formed by combining 25 cations and 8 anions, in the extraction of PDA from aqueous solution were evaluated using COSMO-RS model. The extraction mechanism was investigated with the help of σ-profile and interaction energy analyses. Both the cation and anion have impacts on the extraction efficiency, where cation mainly influences the interaction of IL with PDA and anion affects the hydrophobicity of IL. The IL composed of long alkyl-chain in cation and the anion of [PF6]- or [TF2N]-, which has the σ-profile more likely distributed in the nonpolar region but less distributed in the polar region, is favorable for extraction. The experimental liquid–liquid equilibrium demonstrated the effects of cation and anion on extraction performance, which validated the reliability of COSMO-RS model in IL screening for PDA extraction. The IL [IM-1,8][PF6] could serve as a promising extractant for the downstream separation process of the biological production of PDA.

Solubility of active pharmaceutical ingredients is an important aspect of drug processing and formulation. Although caffeine was a subject of many studies aiming to quantify saturated solutions, many applied solvents suffer from not being environmentally friendly. This work fills this gap by presenting the results of solubility measurements in choline chloride natural deep eutectic solvents, ccNADES, comprising one of seven of the following polyalcohols: glycerol, sorbitol, xylitol, glucose, sucrose, maltose and fructose. The ratio of ccNADES components was optimized for maximizing caffeine solubility at room temperature. Additionally, temperature dependent solubility was measured for the first four systems exhibiting the highest solubility potential, both in their neat forms and in mixtures with water. Results were used for intermolecular interactions assessments using the COSMO-RS-DARE approach, which led to a perfect match between experimental and computed solubility values. An important methodological discussion was provided for an appropriate definition of the systems. Surprising linear trends were observed between the values of fitting parameters and water-ccNADES composition. In addition, comments on selection of the values of the fusion thermodynamic parameters were provided, which led to the conclusion that COSMO-RS-DARE solubility computations can effectively compensate for the inaccuracies of these important physicochemical properties.

The aim of this work was to develop a simple and easy-to-apply model to predict the pH values of deep eutectic solvents (DESs) over a wide range of pH values that can be used in daily work. For this purpose, the pH values of 38 different DESs were measured (ranging from 0.36 to 9.31) and mathematically interpreted. To develop mathematical models, DESs were first numerically described using σ profiles generated with the COSMOtherm software. After the DESs’ description, the following models were used: (i) multiple linear regression (MLR), (ii) piecewise linear regression (PLR), and (iii) artificial neural networks (ANNs) to link the experimental values with the descriptors. Both PLR and ANN were found to be applicable to predict the pH values of DESs with a very high goodness of fit (R2independent validation > 0.8600). Due to the good mathematical correlation of the experimental and predicted values, the σ profile generated with COSMOtherm could be used as a DES molecular descriptor for the prediction of their pH values.

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 separation of benzene and cyclohexane is a challenging process in the petrochemical industry, mainly because of their close boiling points. Extractive separation of the benzene-cyclohexane mixture has been shown to be feasible, but it is important to find solvents with good extractive performance. In this work, 23 eutectic solvents (ESs) containing aromatic components were screened using the predictive COSMO-RS and their respective performance was compared with other solvents. The screening results were validated with experimental work in which the liquid–liquid equilibria of the three preselected ESs were studied with benzene and cyclohexane at 298.5 K and 101.325 kPa, with benzene concentrations in the feed ranging from 10 to 60 wt%. The performance of the ESs studied was compared with organic solvents, ionic liquids, and other ESs reported in the literature. This work demonstrates the potential for improved extractive separation of the benzene-cyclohexane mixture by using ESs with aromatic moieties.

Funding Information: This work was also supported by Associate Laboratory for Green Chemistry–LAQV, financed by national funds from FCT/MCTES (UID/QUI/50006/2020), the contracts of Individual Call to Scientific Employment Stimulus 2020.00835.CEECIND (J.M.M.A.)/2021.01432.CEECIND (A.B.P.) and by FCT/MCTES (Portugal) through the project PTDC/EQU-EQU/29737/2017. The authors thank Solvay for providing the ionic liquid tri(butyl) ethylphosphonium diethylphosphate. M.C.G. and J.A. thank IDEX-LYON for financial support (Programme Investissement d’Avenir ANR-16-IDEX-0005). Publisher Copyright: © 2022 American Chemical Society. All rights reserved. In recent years, the fight against climate change and the mitigation of the impact of fluorinated gases (F-gases) on the atmosphere is a global concern. Development of technologies that help to efficiently separate and recycle hydrofluorocarbons (HFCs) at the end of the refrigeration and air conditioning equipment life is a priority. The technological development is important to stimulate the F-gas capture, specifically difluoromethane (R-32) and 1,1,1,2-tetrafluoroethane (R-134a), due to their high global warming potential. In this work, the COSMO-RS method is used to analyze the solute-solvent interactions and to determine Henry's constants of R-32 and R-134a in more than 600 ionic liquids. The three most performant ionic liquids were selected on the basis of COSMO-RS calculations, and F-gas absorption equilibrium isotherms were measured using gravimetric and volumetric methods. Experimental results are in good agreement with COSMO-RS predictions, with the ionic liquid tributyl(ethyl)phosphonium diethyl phosphate, [P2444][C2C2PO4], being the salt presenting the highest absorption capacities in molar and mass units compared to salts previously tested. The other two ionic liquids selected, trihexyltetradecylphosphonium glycinate, [P66614][C2NO2], and trihexyl(tetradecyl)phosphonium 2-cyano-pyrrole, [P66614][CNPyr], may be competitive as far as their absorption capacities are concerned. Future works will be guided on evaluating the performance of these ionic liquids at an industrial scale by means of process simulations, in order to elucidate the role in process efficiency of other relevant absorbent properties such as viscosity, molar weight, or specific heat. publishersversion published

The risk assessment and control of N-nitrosamine impurities in medicines is a topic of great concern for patients, regulators, and the pharmaceutical industry. This paper discusses a modeling appro...

Utilization of ionic liquids (ILs) for carbon dioxide (CO2) capture is continuously growing, and further understanding of the factors that influence its solubility (notably for new ILs) is crucial. Herein, CO2 absorption of two 1,2,4-triazolium-based ILs was compared with imidazolium-based Ils of different anions, namely bis(trifluoromethylsulfonyl)imide, tetrafluoroborate, and glycinate. The CO2 absorption capacity was determined using an isochoric saturation method and compared with predicted solubility employing COnductor-like Screening Model for Real Solvents (COSMO-RS). To gain an understanding of the effects of cations and anions of the ILs on the CO2 solubility, the molecular orbitals energy levels were calculated using TURBOMOLE. Triazolium-based ILs exhibit higher absorption capacity when compared to imidazolium-based ILs for the same anions. The results also showed that the anions’ energy levels are more determinant towards solubility than the cations’ energy levels, which can be explained by the higher tendency of CO2 to accept electrons than to donate them.

The difficulty synthesizing new co-crystals has made the development of efficient methods for screening co-formers a high priority. Co-crystals have been realized as a new generation of materials w...

COSMO-RS-trained fragment contribution models (FCMs) to predict the partition properties of chlorinated paraffin (CP) congeners were refined and extended. The improvement includes (i) the use of an improved conformer generation method for COSMO-RS, (ii) extension of training and validation sets for FCMs up to C20 congeners covering short-chain (SCCPs), medium-chain (MCCPs) and long-chain CPs (LCCPs), and (iii) more realistic simulation of industrial CP mixture compositions by using a stochastic algorithm. Extension of the training set markedly improved the accuracy of model predictions for MCCPs and LCCPs, as compared to the previous study. The predicted values of the log octanol/water partition coefficients (Kow) for CP mixtures agreed well with experimentally determined values from the literature. Using the established FCMs, this study provided a set of quantum chemically based predictions for 193 congener groups (C10–20 and Cl0–21) regarding Kow, air/water (Kaw), and octanol/air (Koa) partition coefficients, subcooled liquid vapor pressure (VP) and aqueous solubility (Sw) in a temperature range of 5–45 °C as well as the respective enthalpy and internal energy changes.

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).

We have used the COSMOtherm program to estimate activity coefficients and solubilities of mono- and α,ω-dicarboxylic acids and water in binary acid–water systems. The deviation from ideality was found to be larger in the systems containing larger acids than in the systems containing smaller acids. COnductor-like Screening MOdel for Real Solvents (COSMO-RS) underestimates experimental monocarboxylic acid activity coefficients by less than a factor of 2, but experimental water activity coefficients are underestimated more especially at high acid mole fractions. We found a better agreement between COSMOtherm-estimated and experimental activity coefficients of monocarboxylic acids when the water clustering with a carboxylic acid and itself was taken into account using the dimerization, aggregation, and reaction extension (COSMO-RS-DARE) of COSMOtherm. COSMO-RS-DARE is not fully predictive, but fit parameters found here for water–water and acid–water clustering interactions can be used to estimate thermodynamic properties of monocarboxylic acids in other aqueous solvents, such as salt solutions. For the dicarboxylic acids, COSMO-RS is sufficient for predicting aqueous solubility and activity coefficients, and no fitting to experimental values is needed. This is highly beneficial for applications to atmospheric systems, as these data are typically not available for a wide range of mixing states realized in the atmosphere, due to a lack of either feasibility of the experiments or sample availability. Based on effective equilibrium constants of different clustering reactions in the binary solutions, acid dimer formation is more dominant in systems containing larger dicarboxylic acids (C5–C8), while for monocarboxylic acids (C1–C6) and smaller dicarboxylic acids (C2–C4), hydrate formation is more favorable, especially in dilute solutions.

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...

The formation of deep eutectic solvents (DES) is tied to negative deviations to ideality caused by the establishment of stronger interactions in the mixture than in the pure DES precursors. This work tested thymol and menthol as hydrogen bond donors when combined with different flavonoids. Negative deviations from ideality were observed upon mixing thymol with either flavone or flavanone, two parent flavonoids that only have hydrogen bond acceptor (HBA) groups, thus forming non-ionic DES (Type V). On the other hand, the menthol systems with the same compounds generally showed positive deviations from ideality. That was also the case with the mixtures containing the more complex hydroxylated flavonoid, hesperetin, which resulted in positive deviations when mixed with either thymol or menthol. COSMO-RS successfully predicted the behavior of the solid-liquid phase diagram of the studied systems, allowing for evaluation of the impact of the different contributions to the intermolecular interactions, and proving to be a good tool for the design of DES. This research was developed within the scope of the project CICECO-Aveiro Institute of Materials, UIDB/50011/2020, UIDP/50011/2020, and LA/P/0006/2020, and project CIMO-Mountain Research Center, UIDB/00690/2020 and LA/P/0007/2020, financed by national funds through the Portuguese Foundation for Science and Technology/MCTES. Support was also provided by project AllNat—POCI-01-0145-FEDER-030463 (PTDC/EQU-EPQ/30463/2017), funded by FEDER funds through COMPETE2020—Prog. Operacional Competitividade e Internacionalização (POCI), and by national funds through the Foundation for Science and Technology (FCT/MCTES). This work was supported by the Fundacão para a Ciência e Tecnologia (FCT) (funded by national funds through the FCT/MCTES (PIDDAC)) to CIQUP, Faculty of Science, University of Porto (Project UIDB/00081/2020), IMS-Institute of Molecular Sciences (LA/P/0056/2020)). A.I.M.C.L.F. is financed by national funds through the FCT-I.P., in the framework of the execution of the program contract provided in paragraphs 4, 5, and 6 of art. 23 of Law no. 57/2016 of 29 August, as amended by Law no. 57/2017 of 19 July. G.T. and S.M.V.B. acknowledge FCT/MCTES for the Ph.D. grants UI/BD/151114/2021 and SFRH/BD/138149/ 2018, respectively. info:eu-repo/semantics/publishedVersion

In recent years, the fight against climate change and the mitigation of the impact of fluorinated gases (F-gases) on the atmosphere is a global concern. Development of technologies that help to efficiently separate and recycle hydrofluorocarbons (HFCs) at the end of the refrigeration and air conditioning equipment life is a priority. The technological development is important to stimulate the F-gas capture, specifically difluoromethane (R-32) and 1,1,1,2-tetrafluoroethane (R-134a), due to their high global warming potential. In this work, the COSMO-RS method is used to analyze the solute-solvent interactions and to determine Henry's constants of R-32 and R-134a in more than 600 ionic liquids. The three most performant ionic liquids were selected on the basis of COSMO-RS calculations, and F-gas absorption equilibrium isotherms were measured using gravimetric and volumetric methods. Experimental results are in good agreement with COSMO-RS predictions, with the ionic liquid tributyl(ethyl)phosphonium diethyl phosphate, [P2444][C2C2PO4], being the salt presenting the highest absorption capacities in molar and mass units compared to salts previously tested. The other two ionic liquids selected, trihexyltetradecylphosphonium glycinate, [P66614][C2NO2], and trihexyl(tetradecyl)phosphonium 2-cyano-pyrrole, [P66614][CNPyr], may be competitive as far as their absorption capacities are concerned. Future works will be guided on evaluating the performance of these ionic liquids at an industrial scale by means of process simulations, in order to elucidate the role in process efficiency of other relevant absorbent properties such as viscosity, molar weight, or specific heat, This work was also supported by Associate Laboratory for Green Chemistry–LAQV, financed by national funds from FCT/MCTES (UID/QUI/50006/2020), the contracts of Individual Call to Scientific Employment Stimulus 2020.00835.CEECIND (J.M.M.A.)/2021.01432.CEECIND (A.B.P.) and by FCT/MCTES (Portugal) through the project PTDC/EQU-EQU/29737/2017. The authors thank Solvay for providing the ionic liquid tri(butyl) ethylphosphonium diethylphosphate. M.C.G. and J.A. thank IDEX-LYON for financial support (Programme Investissement d’Avenir ANR-16-IDEX-0005)

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 solubility of caffeine in aqueous binary mixtures was measured in five aprotic proton acceptor solvents (APAS) including dimethyl sulfoxide, dimethylformamide, 1,4-dioxane, acetonitrile, and acetone. The whole range of concentrations was studied in four temperatures between 25 °C and 40 °C. All systems exhibit a strong cosolvency effect resulting in non-monotonous solubility trends with changes of the mixture composition and showing the highest solubility at unimolar proportions of organic solvent and water. The observed solubility trends were interpreted based on the values of caffeine affinities toward homo- and hetero-molecular pairs formation, determined on an advanced quantum chemistry level including electron correlation and correction for vibrational zero-point energy. It was found that caffeine can act as a donor in pairs formation with all considered aprotic solvents using the hydrogen atom attached to the carbon in the imidazole ring. The computed values of Gibbs free energies of intermolecular pairs formation were further utilized for exploring the possibility of using them as potential solubility prognostics. A semi-quantitative relationship (R2 = 0.78) between caffeine affinities and the measured solubility values was found, which was used for screening for new greener solvents. Based on the values of the environmental index (EI), four morpholine analogs were considered and corresponding caffeine affinities were computed. It was found that the same solute–solvent structural motif stabilizes hetero-molecular pairs suggesting their potential applicability as greener replacers of traditional aprotic proton acceptor solvents. This hypothesis was confirmed by additional caffeine solubility measurements in 4-formylmorpholine. This solvent happened to be even more efficient compared to DMSO and the obtained solubility profile follows the cosolvency pattern observed for other aprotic proton acceptor solvents.

The solubility of dehydroabietic acid in (−)-α-pinene, p-cymene, (−)-β-caryophyllene, (−)-α-pinene + p-cymene, (−)-β-caryophyllene + p-cymene and (−)-α-pinene + (−)-β-caryophyllene were determined using the laser monitoring method at atmospheric pressure. The solubility of dehydroabietic acid was positively correlated with temperature from 295.15 to 339.46 K. (−)-α-pinene, p-cymene, and (−)-β-caryophyllene were found to be suitable for the solubilization of dehydroabietic acid. In addition, the non-random two liquid (NRTL), universal quasi-chemical (UNIQUAC), modified Apelblat, modified Wilson, modified Wilson–van’t Hoff, and λh models were applied to correlate the determined solubility data. The modified Apelblat model gave the minor deviation for dehydroabietic acid in monosolvents, while the λh equation showed the best result in the binary solvents. A comparative analysis of compatibility between solutes and solvents was carried out using Hansen solubility parameters. The thermodynamic functions of ΔsolH0, ΔsolS0, ΔsolG0 were calculated according to the van’t Hoff equation, indicating that the dissolution was an entropy-driven heat absorption process. The Conductor-like Screening Model for Real Solvents (COSMO-RS) combined with an experimental value was applied to predict the reasonable solubility data of dehydroabietic acid in the selected solvents systems. The interaction energy of the dehydroabietic acid with the solvent was analyzed by COSMO-RS.

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...

Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. We further show that including ReSCoSS conformers significantly improves COSMO-RS based predictions of physicochemical properties over single-conformation approaches. ReSCoSS has found broad adoption in the in-house drug discovery and development work streams and has contributed to establishing quantum-chemistry methods as a strategic pillar in ligand discovery.