Screening Model For Real Solvents Research Articles

Preparation and impregnation of deep eutectic solvents containing zileuton onto adsorbents to elicit the biopharmaceutical attributes

Deep eutectic solvent (DES) is a contemporary and eco-friendly solvent recently exploited to modulate the solubility of drugs. Herein, we developed DESs for an increment of solubility and bioavailability of zileuton (ZLT). ZLT is an anti-inflammatory drug categorized as an inhibitor of the enzyme 5-lipoxygenase commonly prescribed for treating chronic bronchial asthma. However, its therapeutic uses are limited owing to its poor water solubility. Several stable DESs were developed and assessed for viscosity, pH, and solubility. The DES comprising ChCl: EG (1:3) exhibits an excellent ZLT solubility (57.27 ± 0.14 mg/mL). The molecular and electrostatic interaction was assessed through a conductor-like screening model for real solvents (COSMO-RS). Further, 1H NMR analysis, FTIR, and digital microscopy were used to investigate the molecular transition in the chosen DES-ZLT. The DES in a liquid state possesses several drawbacks, such as instability, volatility, and dose precision. Therefore, a wet impregnation approach utilizing inert carriers such as Aerosil-200 and Avicel PH-102 was performed for the solidification of liquid DES. The solidified DES-ZLT was characterized by DSC and PXRD techniques and indicated the existence of ZLT in a highly dissolved state. Furthermore, solid DES-ZLT showed a significant increment in the dissolution studies, resulting in a 2.91 fold rise in oral bioavailability of ZLT. Hence, the presented study proves a well-organized and proficient development of a solid DES system to ameliorate the solubility and stability aspects of ZLT, which could provide the template for promising drugs that lack therapeutic effectiveness owing to solubility issues.

Extraction of ofloxacin from water using hydrophobic eutectic solvents

Wastewater treatment plants do not cope well with emerging micropollutants, such as pharmaceuticals, because they are not effective to remove them. Therefore, this work aims to develop a process for the extraction of ofloxacin (OFX) based on a liquid-liquid extraction using hydrophobic eutectic solvents (HES), coupled with the Conductor-like Screening Model for Real Solvent (COSMO-RS) for solvent screening. First, COSMO-RS was used to predict the partition coefficient of OFX for four HES families: L-menthol: fatty acid, L-menthol: fatty alcohol, fatty acid: fatty acid and fatty acid: fatty alcohols, at three different molar ratios (2:1, 1:1, and 1:2). These results showed that HES formed by fatty acids, especially those with a longer alkyl chain and a higher fatty acid molar ratio, were the most suitable solvents for OFX extraction. Then, the most promising HES to extract OFX was evaluated experimentally. The HES decanoic acid: dodecanoic acid (C10 acid: C12 acid) in a molar ratio of 2:1 being the system with best extraction results of OFX was selected to optimize the extraction conditions of OFX, namely pH, HES: water ratio (v/v), and OFX concentration, using a response surface methodology (RSM). The results obtained showed that at a pH of 5.2, HES-water ratio (v/v) of 1.3, and 2.5 mg/ml of OFX that an extraction efficiency of OFX of (98.8 ± 0.9)% could be achieved. The results show that one-step OFX extraction is possible, but is significantly influenced by both the extraction parameters and the hydrophobic properties of the HES.

Multiscale modeling of CO2 capture in dicationic ionic liquids: Evaluating the influence of hydroxyl groups using DFT-IR, COSMO-RS, and MD simulation methods.

This work employs a combination of density functional theory-infrared (IR), conductor-like screening model for real solvents (COSMO-RS), and molecular dynamic (MD) methods to investigate the impact of hydroxyl functional groups on CO2 capture within dicationic ionic liquids (DILs). The COSMO-RS reveals that hydroxyl groups in DILs reduce the macroscopic solubility of CO2 but improve the selectivity of CO2 over CO, H2, and CH4 gases. Quantum methods in the gas phase and MD simulations in the liquid phase were conducted to delve deeper into the underlying mechanisms. The IR spectrum analysis confirms red shifts in CO2's asymmetric stretching mode and blue shifts in the CR-HR bond of the dication, indicating CO2-DIL interactions and the weakening of the anion-cation interactions caused by the presence of CO2. The results show that the positioning of anions around hydroxyl groups and HR atoms in rings inhibits the proximity of CO2 molecules, causing the hydrogen atoms within methylene groups to accumulate CO2. van der Waals forces were found to dominate the interaction between ions and CO2. The addition of hydroxyl groups strengthens the electrostatic interactions and hydrogen bonds between dications and anions. The stronger interaction energy between ions in [C5(mim)2-(C2)2(OH)2][NTf2]2 limits the displacement of CO2 molecules within this DIL compared to [C5(mim)2-(C4)2][NTf2]2. Compared to [C5(mim)2-(C4)2][NTf2]2, [C5(mim)2-(C2)2(OH)2][NTf2]2 exhibits stronger ion-ion interactions, higher density, and reduced free volume, resulting in a reduction in CO2 capture. These results provide significant insights into the intermolecular interactions and vibrational properties of CO2 in DIL complexes, emphasizing their significance in developing efficient and sustainable strategies for CO2 capture.

Thermophysical insights and COSMO-RS study of triethylenetetramine-based protic ionic liquids with alkyl carboxylic acids

Protic ionic liquids (PILs) have increasing interest due to their potential application compared to conventional organic solvents. In the present study, new class of protic ionic liquids were developed by combining triethylenetetramine as cation and distinct carboxylic acids, specifically formic acid, butanoic acid, hexanoic acid, and octanoic acid employed as the anions. The products structures and purity were verified using 1H and 13C NMR as well as ESI-MS analysis. The structural variations effects on the thermophysical characteristics such as refractive index (nD), viscosity (η), density (ρ), and speed of sound (u) were evaluated throughout a broad temperature range. Temperatures between 293.15 and 333.15 K were used to calculate the viscosity and density values. It was also determined the thermal decomposition temperature (Td) and quantified the amount of water in the synthetic protic ionic liquids. Additional parameters such the expansion coefficient (α), standard entropy (S0), volume (V), lattice potential energy (UPOT), isentropic compressibility (βs), Intermolecular free length (Lf) of PILs were calculated using experimental values for sound speed and density. Furthermore, computation of activation energy employed the experimental viscosity values. In order to calculate the electronic polarizability and free volume present inside the ionic liquids, refractive indices of PILs were measured between the temperatures of 293.15 and 323.15 K. The study also explored the Conductor-like Screening Model for Real Solvents (COSMO-RS) computational approach to gain insights into the structural variation of TETA-based ionic liquids. The prepared PILs derived properties and linked with their structural moieties.

Inhibition of asphaltene aggregation using deep eutectic solvents: COSMO-RS calculations and experimental validation

Asphaltene precipitation/deposition adversely affects various oil and gas processes, such as oil recovery, transportation, and petroleum processing. The resulting increase in viscosity of crude oil decreases distillate yields creating unstable phase separation. Deep eutectic solvents (DESs) have recently gained interest as inhibitors of asphaltene aggregation. The goal of the present study is to derive the mechanism of inhibition of petroleum asphaltene aggregation by a novel screening of DESs. An archipelago-based chemical structure of asphaltene was adopted for performing quantum chemical calculations. The structure was used in the conductor-like screening model for real solvents (COSMO-RS) model to screen potential DESs for asphaltene precipitation. It was found that DESs containing thymol were the most promising of the 153 DES combinations screened. The COSMO-RS predictions were validated experimentally using solubility data of asphaltene in DESs. Among the studied DESs, thymol-diphenyl ether provided the highest solubility for asphaltene, which was further validated using the experimental and the COSMO-RS predicted data. In addition, to characterize the structural interactions between asphaltene and DESs, Fourier transform infrared (FTIR) spectroscopy and nuclear magnetic resonance (NMR) measurements were performed. It was found that strong interaction between asphaltene and the DESs is responsible for the higher asphaltene dispersion. The present approach opens pathways to rationally design and understand the impact of structural variation of DESs based on their interactions with asphaltene.

Experimental and computational studies on isolation of cardanol from cashew nut shell liquid using diethanolamine‐based deep eutectic solvent at different molar ratios

AbstractBACKGROUNDAmine‐based deep eutectic mixtures composed of choline chloride and a DEA‐based hydrogen‐bond donor (HBD) can be used in various molar ratios such as 1:2, 1:3, 1:4, 1:5, 1:6 and 1:7 for isolation of cardanol from cashew nut shell liquid (CNSL).RESULTSIn this study, green techniques were created to extract cardanol from CNSL by utilizing a deep eutectic solvent (DES) based on diethanolamine with various molar ratios [hydrogen‐bond acceptor (HBA): HBD] of 1:2, 1:3,1:4,1:5, 1:6 and 1:7. To enhance cardanol's solubility in DES, promote phase separation, and increase cardanol yield, ethyl acetate (EA) and isobutyl methyl ketone (IBMK) could be utilized as co‐solvents. At temperatures ranging from 293 to 343.15 K and 1 atm, the density of various molar ratios of DES was determined. Additionally, the prepared DES pH behaviour as well as the relationship between pH and temperature were investigated. All investigated DES temperature increases caused a decrease in pH value. By using thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC), similar molar ratios of amine‐based DESs were studied for their thermal stability in terms of decomposition temperature, mass loss and melting temperature. The melting temperature and thermal stability were both increased when the HBD increased. The thermal stability of DES, which mostly depends on intermolecular interactions, is greatly influenced by HBD. Finally, at T = 298.15 K and 1 atm, cardanol was extracted from 50 mL CNSL using different volumes of various molar ratios of DES (100 mL, 75 mL, 50 mL and 25 mL) together with 25 mL IBMK and 25 mL EA. The extracted cardanol was evaluated using Fourier transform infrared spectroscopy and gas chromatography–mass spectrometry.CONCLUSIONIt was observed that the yields of cardanol from each prepared molar ratios ratio of 100 mL DES were 96.57%, 95.38% and 92.87%, respectively. In this study, the sigma potential and sigma profile of chosen HBA and HBD were determined using conductor‐like screening model for real solvents (COSMO‐RS), and the interactions between the molecules during the extraction process were analyzed. The findings demonstrated the viability of using the chosen DESs for the polyphenol extraction process. © 2024 Society of Chemical Industry (SCI).

Extraction of 5-Hydroxymethylfurfural and Furfural in Aqueous Biphasic Systems: A COSMO-RS Guided Approach to Greener Solvent Selection.

5-Hydroxymethylfurfural (HMF) and furfural (Fur) are promising biobased platform chemicals, derived from the dehydration of carbohydrate feedstocks, normally conducted in an aqueous phase. Plagued by side-reactions in such phase, such as the rehydration to levulinic acid (LA) and formic acid (FA) or self-condensation to humins, HMF and Fur necessitates diversification from monophasic aqueous reaction systems toward biphasic systems to mitigate undesired side-reactions. Here, a methodology based on the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) method was used to screen solvent candidates based on the predicted partition coefficients (Ki). Hansen solubility parameters in conjunction with excess thermodynamic quantities determined by COSMO-RS were employed to assess solvent compatibility. Experimental validation of the COSMO-RS values highlighted only minor deviations from the predictions with root-mean-square-error (RMSE) values of HMF and Fur at 0.76 and 5.32, respectively, at 298 K. The combined effort suggested cyclohexanone, isophorone, and methyl isobutyl ketone (MIBK) as the best candidates. Finally, extraction solvent reuse demonstrated cyclohexanone suitability for HMF extraction with KHMF of 3.66 and MIBK for Fur with KFur 7.80 with consistent partitioning across four total runs. Both solvents are classified as recommended by the CHEM21 solvent selection guide, hence adding to the sustainability of the process.

Hybrid Improved Grey Wolf Support Vector Regression Algorithm for Modeling Solubilities of APIs in Pure Ionic Liquids: σ-Profile Descriptors.

The objective of this study was to model the solubility of active pharmaceutical ingredients (APIs) in different ionic liquids (ILs) based on the σ-moments of cations, anions, and APIs that were used as molecular descriptors calculated using the σ-profiles of three categories of descriptors based on conductor-like screening model for real solvents. The database of 83 API-ILs systems composed of 14 APIs, 12 cations, and 7 anions (25 ILs combinations) was collected as 850 data points at different temperature ranges. A hybrid Improved Grey Wolf Support vector regression, abbreviated as I-GWO-SVR(r), algorithm was selected as the learning method. Based on a comprehensive comparison with 11 different models, various statistical factors, and graphical analyses, including an external validation test, analysis of variance (ANOVA), and sensitivity analysis, the capability and validity of the proposed approach have been assessed and verified. The overall study confirmed that the proposed new model provided the best results in terms of predicting the solubility of APIs in ILs.

Predicting sulfanilamide solubility in the binary mixtures using a reference solvent approach.

Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive solubility characteristics of chemical compounds is a non-trivial and demanding process. Therefore, support from theoretical approaches is of practical importance. This study aims to examine the accuracy of the reference solubility approach in the case of sulfanilamide dissolution in a variety of binary solvents. This pharmaceutically active substance has been extensively studied, and a substantial amount of solubility data is available. Unfortunately, using this set of data directly for theoretical modeling is impeded by noticeable inconsistencies in the published solubility data. Hence, this aspect is addressed by data curation using theoretical and experimental confirmations. In the experimental part of our study, the popular shake-flask method combined with ultraviolet (UV) spectrophotometric measurements was applied for solubility determination. The computational phase utilized the conductor-like screening model for real solvents (COSMO-RS) approach. The analysis of the results of solubility calculations for sulfonamide in binary solvents revealed abnormally high error values for acetone-ethyl acetate mixtures, which were further confirmed with experimental measurements. Additional confirmation was obtained by extending the solubility measurements to a series of homologous acetate esters. Our study addresses the crucial issue of coherence of solubility data used for many theoretical inquiries, including parameter fitting of semi-empirical models, in-depth thermodynamic interpretations and application of machine learning protocols. The effectiveness of the proposed methodology for dataset curation was demonstrated for sulfanilamide solubility in binary mixtures. This approach enabled not only the formulation of a consistent dataset of sulfanilamide solubility binary solvent mixtures, but also its implementation as a qualitative tool guiding rationale solvent selection for experimental solubility screening.

Computational study on organochlorine insecticides extraction using ionic liquids

Insecticides pose hazardous environmental effects and can enter the food chain and contaminate water resources. Ionic liquids (ILs) have recently drawn much interest as environmentally friendly solvents and have been an efficient choice for extracting pesticides because of their outstanding thermophysical characteristics and tunable nature. In this study, ILs were screened using COSMO-RS (Conductor-like Screening Model for Real Solvents) to extract organochlorine insecticides from water at 289 K. A total of 165 ILs, a combination of 33 cations with five anions, were screened by COSMO-RS to predict the selectivity and capacity of the organochlorine insecticides at infinite dilution. The Organochlorine insecticide compounds, such as benzene hexachloride (BHC), Heptachlor, Aldrin, Gamma-Chlordane (γ-Chlordane), Endrin, and Methoxychlor are selected for this study. Charge density profiles show that Endrin and Methoxychlor compounds are strong H-bond acceptors and weak H-bond donors, while the rest of the compounds are H-bond donors with no H-bond acceptor potential. Moreover, it has been shown that ILs composed of halides and heteroatomic anions in conjunction with cations have enhanced selectivity and capacity for insecticides. Moreover, the hydrophobic phosphonium-based ILs have enhanced selectivity and capacity for insecticides. In BHC extraction, the selectivity of 1,3-dimethyl-imidazolium chloride was found to be the highest at 1074.06, whereas 2-hydroxyethyl trimethyl ammonium chloride exhibited the highest capacity being 84.0.1,3-dimethyl-imidazolium chloride exhibits the highest performance index, which is 57064.77. In addition, the ILs that have been chosen are well-recognized as environmentally friendly and very effective solvents to extract insecticides from water. As a result, this study evaluated that ILs could be promising solvents that may be further developed for the extraction of insecticides from contaminated water.

Effective removal of personal care product residues from aqueous media using hydrophobic deep eutectic solvents: Experimental and computational approach

Personal care product (PCP) residues - classified under micropollutants (MPs)- are widely found in aquatic environments, posing trace-level toxicity. Traditional water treatment techniques struggle to remove these toxins effectively. Deep eutectic solvents (DESs), the liquid mixtures typically composed of hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs), have recently emerged as a viable alternative for extracting pollutants from water. Among DESs, hydrophobic deep eutectic solvents (HDESs) exhibit low water miscibility and unique solvent properties. The main objective of this study is to synthesize HDESs to effectively eliminate 2-naphthol and methylparaben- two of the significant chemical contaminants in PCPs- from aqueous media. HDESs were prepared by mixing different terpenes (menthol and thymol) and long-chain carboxylic acids at varying molar ratios. They were characterized using different spectroscopic and thermal techniques. The density and viscosity of the pure DESs were measured as afunction of temperature. Experimental studies were carried out using the liquid–liquid extraction (LLE) method, and the factors influencing the efficiency of extraction were optimized.Considering the limited number of studies on the extraction mechanism of MPs from aqueous media, this study employs comprehensive computational methods, including density functional theory (DFT) and the COnductor-like Screening MOdel for Real Solvents (COSMO-RS), to provide a detailed interpretation of the extraction mechanism. A series of successive extractions were conducted to reduce the DES usage to ensure economic viability. The reusability of the best-performed DES was explored. Additionally, the regeneration of one of the DESs was accomplished through activated carbon-based recovery.---------------------------------------------------------------------------------------------------------------------

Sustainable In Silico-Supported Ultrasonic-Assisted Extraction of Oligomeric Stilbenoids from Grapevine Roots Using Natural Deep Eutectic Solvents (NADES) and Stability Study of Potential Ready-to-Use Extracts.

Grapevine roots, as a side-stream of a vineyard, are a sustainable resource for the recovery of oligomeric stilbenoids, such as the bioactive r-viniferin. The aim of this study is to evaluate an in silico-supported method, based on the Conductor-like Screening Model for Real Solvents (COSMO-RS), for selection of environmentally friendly natural deep eutectic solvents (NADES) with regard to the extraction of grapevine roots. The most suitable NADES system for ultrasonic-assisted extraction of r-viniferin was choline chloride/1,2-propanediol. The optimal extraction parameters for r-viniferin were determined using single-factor experiments as follows: choline chloride/1,2-propanediol 1/2 mol/mol, 10 wt% H2O, biomass/NADES ratio 1/10 g/g, and 10 min extraction time. Under optimized conditions, the extraction yield of r-viniferin from grapevine roots reached 76% of the total r-viniferin content. Regarding stability, stilbenoids in choline chloride/1,2-propanediol remained stable during 128 days of storage at ambient temperature. However, fructose/lactic acid-based NADES were observed to degrade stilbenoids; therefore, the removal of the NADES will be of interest, with a suitable method implemented using Amberlite® XAD-16N resin. As green solvents, the NADES have been used as effective and environmentally friendly extractants of stilbenoid-containing extracts from grapevine roots for potential applications in the cosmetic and pharmaceutical industry or as nutraceuticals in the food industry.

Comprehensive Investigation of Cu2+ Adsorption from Wastewater Using Olive-Waste-Derived Adsorbents: Experimental and Molecular Insights.

This study investigates the efficacy of adsorbents from locally sourced olive waste-encompassing olive skins, leaves, and pits, recovered from the initial centrifugation of olives (OWP)-and a composite with sodium alginate (OWPSA) for the removal of Cu2+ ions from synthetic wastewater. Experimental analyses conducted at room temperature, with an initial Cu2+ concentration of 50 mg/L and a solid/liquid ratio of 1 g/L, showed that the removal efficiencies were approximately 79.54% and 94.54% for OWP and OWPSA, respectively, highlighting the positive impact of alginate on adsorption capacity. Utilizing statistical physics isotherm models, particularly the single-layer model coupled to real gas (SLMRG), allowed us to robustly fit the experimental data, providing insights into the adsorption mechanisms. Thermodynamic parameters affirmed the spontaneity and endothermic nature of the processes. Adsorption kinetics were interpreted effectively using the pseudo-second-order (PSO) model. Molecular modeling investigations, including the conductor-like screening model for real solvents (COSMO-RS), density functional theory (DFT), and atom-in-molecule (AIM) analysis, unveiled intricate molecular interactions among the adsorbent components-cellulose, hemicellulose, lignin, and alginate-and the pollutant Cu2+, confirming their physically interactive nature. These findings emphasize the synergistic application of experimental and theoretical approaches, providing a comprehensive understanding of copper adsorption dynamics at the molecular level. This methodology holds promise for unraveling intricate processes across various adsorbent materials in wastewater treatment applications.

Evaluation of amine-based ionic liquids as potential solvents for hydrogen sulfide absorption using COSMO-RS: Computational and experimental validation

Ionic liquids (ILs) is an effective way to convert and remove hydrogen sulfide, H2S from natural gas streams. Amine-based ILs have recently been discovered due to their efficiency of removing H2S due to their excellent characteristics. However, the selection of potential amine-based ILs from a wide range combination of cations and amine-based anions are rather challenging if performed experimentally. Conductor-like Screening Model for Real Solvents (COSMO-RS) was used for the prediction of liquids thermodynamics such as activity coefficient at infinite dilution, selectivity, capacity and performance index (PI) values to evaluate the performance of each amine-based ILs and determine the most efficient ILs for H2S absorption without requiring any experimental data. A total of 42 previously unexplored ionic liquids, amine-based ILs from a combination of 7 amine cations and 6 anions were screened by COSMO-RS model. The findings from COSMO-RS prediction results revealed that ILs without aromatic rings displayed higher efficiencies compared to ILs with aromatic rings. Moreover, N,N,N′,N′-tetramethyl-1,3-propanediamine chloride, [TMPDA][Cl] cation-anion combinations displayed the highest PI value of 52.55 among the screened ILs thus, predicted as the most efficient ILs for H2S absorption. The experimental results obtained validated the COSMO-RS predictions with an approximation of ± 4.51% discrepancies between predicted and experimental data. Hence, it is concluded that COSMO-RS can be used for a reliable pre-experimental prediction and amine-based ILs approach has a huge potential for effective H2S absorption in industrial applications.

Rational design of deep eutectic solvents for the stabilization of dehydrogenases: an artificial neural network prediction approach.

Stabilized enzymes are crucial for the industrial application of biocatalysis due to their enhanced operational stability, which leads to prolonged enzyme activity, cost-efficiency and consequently scalability of biocatalytic processes. Over the past decade, numerous studies have demonstrated that deep eutectic solvents (DES) are excellent enzyme stabilizers. However, the search for an optimal DES has primarily relied on trial-and-error methods, lacking systematic exploration of DES structure-activity relationships. Therefore, this study aims to rationally design DES to stabilize various dehydrogenases through extensive experimental screening, followed by the development of a straightforward and reliable mathematical model to predict the efficacy of DES in enzyme stabilization. A total of 28 DES were tested for their ability to stabilize three dehydrogenases at 30°C: (S)-alcohol dehydrogenase from Rhodococcus ruber (ADH-A), (R)-alcohol dehydrogenase from Lactobacillus kefir (Lk-ADH) and glucose dehydrogenase from Bacillus megaterium (GDH). The residual activity of these enzymes in the presence of DES was quantified using first-order kinetic models. The screening revealed that DES based on polyols serve as promising stabilizing environments for the three tested dehydrogenases, particularly for the enzymes Lk-ADH and GDH, which are intrinsically unstable in aqueous environments. In glycerol-based DES, increases in enzyme half-life of up to 175-fold for Lk-ADH and 60-fold for GDH were observed compared to reference buffers. Furthermore, to establish the relationship between the enzyme inactivation rate constants and DES descriptors generated by the Conductor-like Screening Model for Real Solvents, artificial neural network models were developed. The models for ADH-A and GDH showed high efficiency and reliability (R2 > 0.75) for in silico screening of the enzyme inactivation rate constants based on DES descriptors. In conclusion, these results highlight the significant potential of the integrated experimental and in silico approach for the rational design of DES tailored to stabilize enzymes.

Natural deep eutectic solvents for turbidity removal from synthetic pharmaceutical wastewater

Contamination of water resources by active pharmaceutical ingredient wastes is among major environmental concerns. To prevent major disruptions of aquatic life, an efficient and environmentally-friendly turbidity removal procedure of common contaminants such as paracetamol should be established. In this study, several natural deep eutectic solvents (NADESs) were screened to reduce the turbidity of simulated water contaminated with paracetamol below the standard turbidity limit recommended by the National Water Quality Standards for Malaysia (50 NTU). The optimal operating parameters (NADES dosage, stirring time and operating pH) were determined. Under optimized conditions, stearic acid-based NADES achieved the highest turbidity removal of 97.5 %. High coagulation performances were investigated based on molecular interaction using COSMO-RS (COnductor like Screening MOdel for Real Solvents) ?-profile and ?-potential (histogram of charge density distribution over molecular surface) and showed high affinity between the NADES compounds and paracetamol. Thus, NADESs are promising candidates for turbidity removal of paracetamol from water and are viable in further investigations for effluent treatment applications.

Highly Concentrated Electrolytes for Lithium Sulfur Batteries – the Role of the Anion(s)

Lithium-sulfur batteries (Li-S) have attracted a lot of attention as a alternative/complement to lithium-ion batteries (LIBs) – due to both high energy density, availability, and inexpensive materials used.[1]Yet, dissolution of sulfur from the C/S cathode and subsequent shuttling of lithium polysulfides (LiPS) to the anode as well as the instability of the Li metal anode itself are true scientific and technological challenges. Advancing in the field of electrolytes is one promising way to overcome both issues.Switching from the standard 1 M electrolyte design of LIBs to highly concentrated electrolytes (HCEs) may both prevent the dissolution of LiPSs and hinder dendrite formation at the lithium metal anode.[2]Here we combine experimental methods and computational approaches to investigate several HCEs based on various Li-salts in several standard organic solvents. Experimentally we targeted electrochemical properties, local electrolyte structure, and physico-chemical properties, with focus on the role(s) of the Li-salt anions. Furthermore, to predict the solubility of sulfur the conductor like screening model for real solvents (COSMO-RS), a computational fluid phase thermodynamic approach, was used.[3] Overall, the challenges and opportunities associated with the use of HCEs in Li-S batteries will be addressed, also highlighting potential areas for future research and development.References Peng et al., "Drastic effect of salt concentration in ionic liquid on performance of lithium sulfur battery." Journal of the Electrochemical Society 169.5 (2022): 050515.Suo et al., "A new class of solvent-in-salt electrolyte for high-energy rechargeable metallic lithium batteries." Nature communications 4.1 (2013): 1481.Jeschke and P. Johansson, "Predicting the Solubility of Sulfur: A COSMO‐RS‐Based Approach to Investigate Electrolytes for Li–S Batteries." Chemistry–A European Journal 23.38 (2017): 9130-9136.

Extraction of Pyrrole from Its Mixture with n-Hexadecane Using Ionic Liquids and Their Binary Mixtures.

The conventional hydrodenitrogenation method is expensive and involves the use of catalysts and harsh procedures. In the last few years, ionic liquids (ILs) have gained attention as a promising alternative solvent for fuel oil extractive denitrogenation. In this work, the Conductor-like Screening Model for Real Solvents (COSMO-RS) was used to screen 173 potential ILs as solvents for fuel oil. Two ILs (1-ethyl-3-methylimidazolium dicyanamide ([EMIM][N(CN)2]) and 1-ethyl-3-methylimidazolium methanesulfonate ([EMIM][MeSO3])) were selected for experimental investigation. The experimental liquid-liquid extraction of pyrrole (taken as the model nitrogen compound) from n-hexadecane (the model fuel) was conducted at 298 K and 1 atm with feed concentrations of pyrrole ranging from 10 to 50 wt%, using either the two pure ILs or their mixtures with dimethylformamide or ethylene glycol. Moreover, the NRTL model was effectively used to correlate the experimental tie lines. This work shows that the use of a binary mixture of ILs with a conventional solvent results in good selectivity, but has a low capacity for extracting pyrrole compounds. On the other hand, using an IL-IL mixture exhibits good results for both capacity and selectivity. All the ternary systems tested showed positive slopes, indicating that the nitrogen compounds had a higher affinity for the IL and binary mixture extract phase. In fact, the extraction efficiency for all the systems shows promising results. This characteristic is advantageous, as it requires less solvent to remove nitrogen compounds.

Scaled water sigma potential as a descriptor of LCST and UCST behavior in aqueous ionic liquid solutions

This study introduces the scaled sigma potential of water (σr), a new metric using the COSMO-RS (Conductor like Screening Model for Real Solvents) framework, as a descriptor of upper and lower critical solution temperature (UCST and LCST) governed phase separation in aqueous ionic liquid (IL) solutions. The maximum and minimum values of σr correspond to the homogenous and phase separated states, at a given composition, for both UCST and LCST cases. Furthermore, the value of σr changes from positive to negative as the temperature increases in LCST exhibiting solutions, while as the temperature increases in UCST exhibiting solutions, the value of σr changes from negative to positive. Therefore, σr provides a less computationally intensive alternate to Gibbs free energy calculations and to the generation of phase diagrams for assessing UCST/LCST behavior in aqueous IL solutions.

A green approach for genistein and apigenin extraction optimization from by-products of soybean crops

Soybeans’ genistein and its isomer apigenin are widely studied bioactive compounds owing to their therapeutic potential for treating various health disfunctions. A green extraction of both from soy by-products could lead to a valuable and sustainable approach to adding value to these materials in a biorefinery context. Here Hansen Solubility Parameters (HSP) and the Conductor-like Screening MOdel for Real Solvents (COSMO-RS) were applied to screen green molecular solvents and Natural Eutectic Solvents for the extraction of genistein and apigenin from soy by-products. The predicted solubilities of genistein and apigenin in 18 shortlisted candidates were experimentally tested by dynamic maceration, the most industrially implemented natural products extraction technique. EtOH:H2O (8:2, v/v) and natural eutectic solvent (NAES) betaine:ethylene glycol (1:2, mol/mol) showed the highest performance. These were selected for extraction optimizations by Design of Experiments from soy branches, the largest by-product by mass. The optimum condition of each solvent was applied to extract all other parts of soy collected post-mechanical harvesting. The highest value of apigenin, 591.49 ± 26.7 μg/g, was achieved from soy pods with EtOH:H2O (8:2, v/v), while the highest of genistein, 54.04 ± 3.39 μg/g, was achieved from soybeans using the same solvent. Our findings highlight the necessity of exercising caution when interpreting in silico outcomes in the context of metabolite extractions from complex matrices. A trade-off between in silico solvent screening and experimental work should be followed when developing new phytochemical extraction processes. Furthermore, soy by-products emerged as competitive candidates for a long-term source of the bioactive apigenin in a biorefinery context.