Conductor-like Screening Model Research Articles

Ionic liquid promoted extraction of gold(III) from electronic waste: a modeling study

ABSTRACT Being an expensive metal, the large-scale requirement of gold in the ever-growing market of electronics increases the overall cost of manufacturing. Hence, recycling gold from electronic waste mitigates the demand and subsequently bounds the price of electronic goods. However, the extraction of gold from electronic waste poses a severe hazard to the environment. Because of tuneable and fascinating properties, ionic liquids (ILs) have emerged as state-of-the-art solvents to extract gold from electronic waste. Herein, the modeling of IL-assisted liquid-liquid-extraction incorporating UNIQUAC extended Pitzer–Debye–Hückel* (PDH*) thermodynamic model has been used for the extraction process of gold from an aqueous acidic solution. The long-range, weak electrostatic interactions present in ionic liquids are adequately represented by the extended PDH* model. The model parameters are obtained from the polarizable continuum medium (PCM) calculation, conductor-like screening model for real solvent (COSMO-RS), and genetic algorithm formulation. Altogether, 11 hydrophobic ILs consisting of 9 imidazolium, 1 pyrrolidinium, and 1 ammonium class with 51 tie line data points are considered for the modeling. The estimated root mean square deviation of 0.002–0.99% over 51 tie lines reveals the goodness of the fitting. The projected percentage extraction efficiency lies in the range of 98.5% to 99.3%.

The role of quantum-chemical descriptors and sigma-profile overlapping of different co-solvents on tuning ethanolic extraction of soybean oil

Co-solvents can significantly improve ethanol efficiency in vegetable oil extraction, making their use a viable, cost-effective, and sustainable alternative to conventional solvents. The challenge, however, is to understand the complex interactions between the solvents and how this can affect the yield and quality of the extracted oil. In this study, the COnductor-like Screening Model with Segment Activity Coefficient and Hansen solubility parameters were combined and used to optimize soybean oil extraction using ethanol along with seven different co-solvents. In parallel, an experimental approach was carried out to verify the accuracy of the models. Both theoretical and empirical results indicated that the oil extraction yield decreased as the co-solvent polarity increased. The best performance in solubilizing non-polar lipids was observed for the mixture of 10 wt% of p-cymene, a non-polar solvent, with 90 wt% ethanol, reaching a yield of 24.35 g/100 g. According to the thermodynamic analysis, the effects of polarity weigh heavily on the standard entropy, which rules the driving force of mass transfer during the extraction. The interaction mechanisms were carefully investigated employing quantum mechanical calculations, revealing how the differences in chemical potential (μ), hardness (η), and electrophilicity (ω) underlie the macroscopic results and rule the efficiency obtained for different solvent ratios and combinations.

Predictive understanding of the surface tension and velocity of sound in ionic liquids using machine learning.

Knowledge of the physical properties of ionic liquids (ILs), such as the surface tension and speed of sound, is important for both industrial and research applications. Unfortunately, technical challenges and costs limit exhaustive experimental screening efforts of ILs for these critical properties. Previous work has demonstrated that the use of quantum-mechanics-based thermochemical property prediction tools, such as the conductor-like screening model for real solvents, when combined with machine learning (ML) approaches, may provide an alternative pathway to guide the rapid screening and design of ILs for desired physiochemical properties. However, the question of which machine-learning approaches are most appropriate remains. In the present study, we examine how different ML architectures, ranging from tree-based approaches to feed-forward artificial neural networks, perform in generating nonlinear multivariate quantitative structure-property relationship models for the prediction of the temperature- and pressure-dependent surface tension of and speed of sound in ILs over a wide range of surface tensions (16.9-76.2 mN/m) and speeds of sound (1009.7-1992m/s). The ML models are further interrogated using the powerful interpretation method, shapley additive explanations. We find that several different ML models provide high accuracy, according to traditional statistical metrics. The decision tree-based approaches appear to be the most accurate and precise, with extreme gradient-boosting trees and gradient-boosting trees being the best performers. However, our results also indicate that the promise of using machine-learning to gain deep insights into the underlying physics driving structure-property relationships in ILs may still be somewhat premature.

Assessment of physicochemical properties of sorbent materials in passive and active sampling systems towards gaseous nitrogen-containing compounds

The adsorption and desorption behavior of volatile nitrogen-containing compounds in vapor phase by solid-phase microextraction Arrow (SPME-Arrow) and in-tube extraction (ITEX) sampling systems, were investigated experimentally using gas chromatography-mass spectrometry. Three different SPME-Arrow coating materials, DVB/PDMS, MCM-41, and MCM-41-TP and two ITEX adsorbents, TENAX-GR and MCM-41-TP were compared to clarify the selectivity of the sorbents towards nitrogen-containing compounds. In addition, saturated vapor pressures for these compounds were estimated, both experimentally and theoretically. In this study, the adsorption of nitrogen-containing compounds on various adsorbents followed the Elovich model well, while a pseudo-first-order kinetics model best described the desorption kinetics. Pore volume and pore sizes of the coating sorbents were essential parameters for the determination of the adsorption performance for the SPME-Arrow sampling system. MCM-41-TP coating with the smallest pore size gave the slowest adsorption rate compared to that of DVB/PDMS and MCM-41 in the SPME-Arrow sampling system. Both adsorbent and adsorbate properties, such as hydrophobicity and basicity, affected the adsorption and desorption kinetics in SPME-Arrow system. The adsorption and desorption rates of studied C6H15N isomers in the MCM-41 and MCM-41-TP sorbent materials of SPME-Arrow system were higher for dipropylamine and triethylamine (branched amines) than for hexylamine (linear chain amines). DVB/PDMS-SPME-Arrow gave fast adsorption rates for the aromatic-ringed pyridine and o-toluidine. All studied nitrogen-containing compounds demonstrated high desorption rates with DVB/PDMS-SPME-Arrow. Chemisorption and physisorption were the sorption mechanisms in MCM-41- and MCM-41-TP- SPME-Arrow, but additional experiments are needed to confirm this. An active sampling technique ITEX gave comparable adsorption and desorption rates on the selective MCM-41-TP and universal TENAX-GR sorbent materials for all the compounds studied. Vapor pressures of nitrogen-containing compounds were experimentally estimated by using retention index approach and these values were compared with the theoretical ones, calculated using the COnductor-like Screening MOdel for Real Solvent (COSMO-RS) model. Both values agreed well with those found in the literature proving that these methods can be successfully used in predicting VOC's vapor pressures, e.g. for the formation of secondary organic aerosols.

How to apply terpenoid-based deep eutectic solvents for removal of antibiotics and dyes from water: Theoretical prediction, experimental validation and quantum chemical evaluation

This study proposed a theoretical prediction method and mechanism investigation for the extraction of antibiotics and dyes from aqueous media using terpenoid-based deep eutectic solvents (DESs). Firstly, Conductor-like Screening Model for Real Solvents (COSMO-RS) approach was applied to predict selectivity, capacity and performance index in the extraction of 15 target compounds including antibiotics (tetracyclines, sulfonamides, quinolones, β-lactams) and dyes by 26 terpenoid-based DESs, and thymol-benzyl alcohol shows promising theoretical selectivity and extraction efficiency for the target compounds. Moreover, the structures of both hydrogen bond acceptors (HBA) and hydrogen bond donors (HBD) have an impact on the predicted extraction performance, which can be improved by tailoring those candidates with higher polarity, smaller molecular volume, shorter alkyl chain length and the presence of aromatic ring structures, etc. According to the predicted molecular interactions revealed by σ-profile and σ-potential, the DESs with HBD ability can promote the separation process. Furthermore, reliability of proposed prediction method was confirmed by experimental verification, indicating that the trends of theoretical extraction performance index were similar with the experimental results by using actual samples. At last, the extraction mechanism was evaluated by quantum chemical calculations based on visual presentations, thermodynamic calculations and topological properties; and the target compounds showed favorable energies of solvation to transfer from aqueous phase to DESs phase. The proposed method has been proved with potential to provide the efficient strategies and guidance for more applications (e.g., microextraction, solid phase extraction, adsorption) with similar molecular interactions of green solvents in environmental research.

Multicriteria design of novel natural hydrophobic deep eutectic solvents for the extraction of perfluoroalkyl acids using COSMO-RS

In this study, a molecular modeling approach was used to identify the most effective natural hydrophobic deep eutectic solvents (HDESs) for extracting the emerging pollutants, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) from synthetic wastewater. The use of HDESs for this purpose has not been reported in the literature, making this a pioneering contribution to the field. First, an extensive literature search was conducted to generate a list of 74 non-ionic HDES constituents. In the second step, a systematic screening of natural components was conducted to identify 55 new compounds that can be used for the synthesis of HDESs. The Conductor-like Screening Model for Real Solvents (COSMO-RS) was then used to screen the 129 potential HDES constituents based on three key performance indicators: distribution ratio, selectivity, and performance index at infinite dilution compared to the predicted performance of toluene as a benchmark, as the use of molecular solvents or DESs for this purpose has never been reported in the literature. The top 20 HDES constituents with the highest extraction performance were predominantly from the terpene and terpenoid families. The median lethal dose was also used to analyze toxicity. A multicriteria evaluation approach was adopted to evaluate several properties important to liquid–liquid extraction (LLE) processes, including the extraction performance, density, vapor pressure, water solubility, and leachability of DESs. Three HDESs, namely, trioctylphosphine oxide: 2-methylbenzothiazole (1:9), trioctylphosphine oxide: menthyl acetate (1:4), and 1,8-cineole: menthyl acetate (2.5:1), showed promising results. This study provides molecular insights on extracting PFOA/PFOS from wastewater using HDESs and emphasizes the need to evaluate LLE units using multicriteria. In addition, the results may serve as a starting point for further research, including the synthesis and characterization of novel HDES constituents and the development of optimized HDESs for the extraction of PFOA/PFOS from wastewater.

A computational and experimental investigation of TEOS-treated graphene oxide-PVA interaction: Molecular dynamics simulation and COSMO-RS insights

This research investigates the effect of tetraethyl orthosilicate TEOS on the interaction mechanism in the hybrid polyvinyl alcohol (PVA)/graphene oxide (GO) material. PVA, PVA/Go, and PVA/GO-SiO2 are produced by the solution casting method. The TEOS treated GO is confirmed by FTIR and also suggests that PVA is chemically bonded to GO-SiO2. XRD results reveal that the crystallinity of PVA is significantly reduced with the addition of TEOS as it becomes completely amorphous and shows that the GO has a full exfoliation in the matrix. However, thermogravimetric analysis indicates that the incorporation of GO improves the thermal stability of PVA by reducing its mass-loss rate upon heating. Theoretical molecular dynamic simulations indicate that the addition of SiO2 could significantly improve the binding interaction energies from 14387 kcal/mol to 15039 kcal/mol for 6PVA/3GO and 6PVA/3GO-3SiO2 systems, respectively. These simulations also highlight the occurrence of a hydrogen bonding between PVA and GO oxygen groups and PVA and Si-OH groups. The Conductor-like Screening Model for Real Solvents (COSMO-RS) study shows the intermediary role played by SiO2, which increases the compatibility between PVA and GO. The theoretical blend study also led to the conclusion that the three molecules could be mixed over the entire temperature range. Overall, these results suggest that TEOS can be successfully employed for the functionalization of PVA/GO hybrid materials, as it strengthens the interaction of the organic and inorganic phases.

COSMO-RS predictive screening of type 5 hydrophobic deep eutectic solvents for selective platform chemicals absorption

Platform chemicals are crucial to the development of designer chemicals in industry; however, the utilization of these chemicals is limited from requiring separation from an aqueous phase. Type 5 hydrophobic deep eutectic solvents (HDES) have recently proven their ability to extract various low concentration solutes from aqueous solution. However, identifying a suitable HDES experimentally is a daunting task due to the large number of hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), and their mixing ratio, with the HDES being ever increasing. In this study, Conductor-like Screening MOdel for Real Solvents (COSMO-RS) was utilized for over one hundred HDES and their relative solubilization ability for sorbitol, 5-hydroxymethyl furfural, and levulinic acid. Moreover, energetic mechanisms of solubilization were analyzed through the prediction of sigma profiles, sigma potentials, activity coefficients, and excess enthalpy of absorption. COSMO-RS results show that HBAs with tetra alkyl chains and amino acid-based HBDs are suitable HDES components for absorbing sorbitol, 5-hydroxymethyl furfural, and levulinic acid through a combination of van der Waals and hydrogen bonding interactions. These interactions are quantitatively examined through calculated excess enthalpy predictions, for example tetrabutylammonium bromide and arginine with a compositional ratio of 8:1, respectively, had an excess enthalpy of mixing with HMF of −7.9 kcal/mol despite the steric hindrance factor valuing ∼ 4.0 kcal/mol.

Extraction of artemisinin using natural deep eutectic solvent selected by COSMO-RS

Natural deep eutectic solvent (NADES) has become an alternative and environmentally friendly solvent. This study designed new eutectic systems for the extraction of artemisinin from the leaves of Artemisia annua L. with the aid of conductor-like screening model for real solvents (COSMO-RS). The performance of the benzoic acid/fenchyl alcohol-based NADES was studied comprehensively under different extraction conditions, including hydrogen-bond donor (HBD)/hydrogen-bond acceptor (HBA) molar ratio, solid-liquid ratio, extraction temperature, and extraction time. It was found that artemisinin extraction should be performed using HBD/HBA 1:4 at 50 °C within 1.5 h. The extraction yield of the target could reach 11.08 mg/g. Artemisinin and the NADES were recovered from the final extract. Furthermore, the extraction mechanism was elucidated by the combination of 1H nuclear magnetic resonance (1H NMR) and scanning electron microscopy (SEM). The hydrogen bond reformation and the plant tissue destruction play vital roles during the extraction process. Therefore, the proposed NADES could serve as a green solvent to effectively extract natural bioactive compounds. The application of the NADESs proved their promise as designable solvents with stronger extraction capabilities than traditional organic solvents.

COSMO prediction of siloxane compounds absorption on type 3 and type 5 deep eutectic solvents

This study reports a Conductor-like Screening MOdel for Real Solvents (COSMO-RS) prediction for 151 type 3 (polar) and type 5 Deep Eutectic Solvents (DES, non-polar) for absorption of hexamethyldisiloxane, octamethyltrisiloxane, hexamethylcyclotrisiloxane, and octamethylcyclotetrasiloxane. Through the examination of generated sigma surfaces, sigma profiles, and sigma potentials, it was found that while the siloxane chains offer sufficiently strong hydrogen bond accepting sites, the steric hindrance of the methyl groups cause less polar solvents (type 5) to outperform the more polar ones (type 3). The thermodynamic study predicts thymol-based type 5 DES as significantly more affinitive for siloxane compounds than common conventional solvents (DEA, MEA, MDEA, menthol, and DPEG Blend) with lnγ activity coefficients reaching low as −0.64. Enthalpy of mixing study shows Vander Waals interactions dominate DES-siloxane compound interactions over hydrogen bonding by over 10x enthalpic release, clarifying discrepancy in literature on how siloxanes are solvated by DES. Thymol: Stearic acid (4:1) showed the lowest excess enthalpy of mixing at −10.4 kcal/mol. An environmental health and safety (EHS) study show the best performing DES components (camphor, capric acid, lauric acid, myristic acid, stearic acid, undecenoic acid, borneol, betaine, hexadecanoic acid, and thymol) are potentially environmentally benign and safe for operation procedures.

Co-Former Screening Method for Multicomponent Crystals Based on Partial Least Squares Regression: A Case Study of Ciprofloxacin

Multicomponent crystal is an effective way to improve the physicochemical properties of drugs. However, screening for co-formers that form multicomponent crystals with active pharmaceutical ingredients is still a challenge. In this study, a co-former prediction method based on partial least squares (PLS) regression was developed. First, 101 positive and negative samples reported were traced from the literature as a training set, based on which seven prediction models were built. Ciprofloxacin (CIP) was selected as the model drug, and the prediction models developed were adopted to predict co-formers which might form multicomponent crystals with CIP. Seven CIP multicomponent crystal systems were successfully prepared experimentally, six of which were hit by the two-parameter prediction model with the Hansen solubility parameter and the conductor-like screening model for real solvents, which achieved an overall accuracy and positive accuracy of 85 and 75%, respectively, higher than those of other models. All seven multicomponent crystal systems showed an increase in process solubility in pH 6.8 phosphate buffer solution (1.06–3.92-fold) and exhibited two different types of dissolution behaviors, wherein three samples exhibited a supersaturated peak in the dissolution process, while the other four did not. This difference was mainly due to the different rates of CIP trihydrate precipitation. The hygroscopic stability of all multicomponent crystals at room temperature and 95% relative humidity was substantially improved compared to raw CIP. This study provides a simple and effective strategy for the predictive screening of multicomponent crystal systems.

Tailoring Deep Eutectic Solvents to Provoke Solubility and Bioavailability of Naringin: Implications of a Computational Approach.

Recently, the applications of deep eutectic solvents (DESs) as green and sustainable solvents for the solubilization of functional foods and phytophenols have dramatically risen concerning global issues on the utilization of organic solvents. Nevertheless, developing a suitable DES system for phytocomponents to enhance its solubility and bioavailability is complex and requires a sound experimental setup. Herein, we have attempted to develop DES encompassing the choline chloride (ChCl) along with oxalic acid (OA), l-glutamine (l-Glu), urea (U), and glycerol (Gro) at different ratios to elicit the solubility and bioavailability of naringin (NAR). Several DES systems were designed and tested for solubility, kinematic viscosity, and pH. Among these, DES-NAR encompassing ChCl/Gro in a 1:3 ratio exhibited the maximum solubility of NAR (232.56 ± 7.1 mg/mL) and neutral characteristic and thus considered suitable for NAR. Further, the conductor-like screening model for real solvents (COSMO-RS) has been employed to estimate the molecular and electrostatic interactions. DES-NAR was evaluated by polarized optical microscopy, Fourier-transform infrared (FTIR), differential scanning calorimetry (DSC), and 1H NMR to investigate the molecular transition and interaction. Further, diffusion and permeability studies were performed, which suggest significant improvements in DES-NAR. Likewise, the pharmacokinetic studies revealed a two times increase in the oral bioavailability of NAR in a designed DES system. Thus, the work represents a systematic and efficient development of the DES system for a potential phytocomponent considering the biosafety impact, which may widen the interest in pharmaceutical and food sciences.

Structural Sampling and Solvation Models for the Simulation of Electronic Spectra: Pyrazine as a Case Study

The impact of sampling methods on spectral broadening in the gas phase and on the convergence of spectra in aqueous solution when using microsolvation, continuum solvation, and hybrid models is studied using pyrazine as a test case. For the sake of comparing classical Maxwell-Boltzmann and Wigner samplings in the gas phase, static and time-resolved X-ray absorption spectra after photoexcitation to the lowest 1B2u(ππ*) state, as well as the static UV-vis absorption spectrum, are considered. In addition, the UV-vis absorption spectrum of pyrazine in aqueous solution is also computed in order to systematically investigate its convergence with the number of explicitly included solvent shells with and without taking bulk solvation effects into account with the conductor-like screening model to represent implicit water beyond such explicit solute complexes. Concerning the static and time-resolved X-ray absorption spectra of pyrazine at the carbon K-edge as well as its UV-vis absorption spectrum in the gas phase, we find that these spectra obtained with Wigner and Maxwell-Boltzmann samplings substantially agree. For the UV-vis absorption spectrum in the aqueous solution, only the first two energetically low-lying bands converge quickly with the size of the explicitly included solvation shells, either with or without an additional continuum solvation taken into account. In stark contrast, calculations of the higher-lying excitations relying on finite microsolvated clusters without additional continuum solvation severely suffer from unphysical charge-transfer excitations into Rydberg-like orbitals at the cluster/vacuum interface. This finding indicates that computational UV-vis absorption spectra covering sufficiently high-lying states converge only if continuum solvation of the explicitly microsolvated solutes is included in the models.

COSMO-SAC and QSPR combined models: A flexible and reliable strategy for screening the extraction efficiency of deep eutectic solvents

At present, the composition of deep eutectic solvents (DESs) is usually screened by trial and error, which requires a lot of experimental time and reagent consumption. A hierarchical DESs screening method was proposed in this work and used to develop a fast, cost-effective, and pollution-free method to extract oleocanthal from extra virgin olive oil (EVOO). The extractive performance of 220 DESs were predicted by the thermodynamic model Conductor-like Screening Model for Segment Activity Coefficient (COSMO-SAC), while their melting point (Tm) and viscosity (η) were evaluated by the regressed solid–liquid equilibria (SLE) diagram and Quantitative Structure-Property Relationship (QSPR) models, respectively. Choline chloride (ChCl)/phenol was found to be the best DES candidate due to its high infinite dilution distribution ratio of oleocanthal (C∞=1.89g/g) and excellent physical properties (Tm=243.02 K and η=39.70cP). The screening results were confirmed by comparing the predicted thermophysical properties with the experimental ones and the extraction conditions were optimized. The extraction efficiency of oleocanthal was 59.54 μg/g, higher than the acetonitrile (19.90%) and conventional DES methods composed of ChCl, xylitol and water (21.94%), significantly reduced the solvent consumption and extraction duration. The flexible and reliable DESs screening models established in this paper can reduce the experimental workload, and provides a new idea for the efficient extraction of trace components, which has extensive reference significance.

Experimental and Computational Evaluation of 1,2,4-Triazolium-Based Ionic Liquids for Carbon Dioxide Capture

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.

Solid–Liquid Equilibrium in Co-Amorphous Systems: Experiment and Prediction

In this work, the solid-liquid equilibrium (SLE) of four binary systems combining two active pharmaceutical ingredients (APIs) capable of forming co-amorphous systems (CAMs) was investigated. The binary systems studied were naproxen-indomethacin, naproxen-ibuprofen, naproxen-probucol, and indomethacin-paracetamol. The SLE was experimentally determined by differential scanning calorimetry. The thermograms obtained revealed that all binary mixtures investigated form eutectic systems. Melting of the initial binary crystalline mixtures and subsequent quenching lead to the formation of CAM for all binary systems and most of the compositions studied. The experimentally obtained liquidus and eutectic temperatures were compared to theoretical predictions using the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and conductor-like screening model for real solvents (COSMO-RS), as implemented in the Amsterdam Modeling Suite (COSMO-RS-AMS). On the basis of the obtained results, the ability of these models to predict the phase diagrams for the investigated API-API binary systems was evaluated. Furthermore, the glass transition temperature (Tg) of naproxen (NAP), a compound with a high tendency to recrystallize, whose literature values are considerably scattered, was newly determined by measuring and modeling the Tg values of binary mixtures in which amorphous NAP was stabilized. Based on this analysis, erroneous literature values were identified.

Ionic Liquid-Based Green Emulsion Liquid Membrane for the Extraction of the Poorly Soluble Drug Ibuprofen

Ibuprofen (Ibf) is a biologically active drug (BADs) and an emerging contaminant of concern (CECs) in aqueous streams. Due to its adverse effects upon aquatic organisms and humans, the removal and recovery of Ibf are essential. Usually, conventional solvents are employed for the separation and recovery of ibuprofen. Due to environmental limitations, alternative green extracting agents need to be explored. Ionic liquids (ILs), emerging and greener alternatives, can also serve this purpose. It is essential to explore ILs that are effective for recovering ibuprofen, among millions of ILs. The conductor-like screening model for real solvents (COSMO-RS) is an efficient tool that can be used to screen ILs specifically for ibuprofen extraction. The main objective of this work was to identify the best IL for the extraction of ibuprofen. A total of 152 different cation-anion combinations consisting of eight aromatic and non-aromatic cations and nineteen anions were screened. The evaluation was based upon activity coefficients, capacity, and selectivity values. Furthermore, the effect of alkyl chain length was studied. The results suggest that quaternary ammonium (cation) and sulfate (anion) have better extraction ability for ibuprofen than the other combinations tested. An ionic liquid-based green emulsion liquid membrane (ILGELM) was developed using the selected ionic liquid as the extractant, sunflower oil as the diluent, Span 80 as the surfactant, and NaOH as the stripping agent. Experimental verification was carried out using the ILGELM. The experimental results indicated that the predicted COSMO-RS and the experimental results were in good agreement. The proposed IL-based GELM is highly effective for the removal and recovery of ibuprofen.

A-Priori screening of deep eutectic solvent for enhanced oil recovery application using COSMO-RS framework

This study investigates the potential of Deep Eutectic Solvent (DES) in Enhanced Oil Recovery (EOR) via interfacial tension (IFT) reduction mechanism. The effectiveness of 217 DES in the IFT reduction mechanism that ultimately assist in EOR is investigated via COnductor-like Screening MOdel for Real Solvent (COSMO-RS) theory and the sigma moment model. Genetic algorithm (GA) is employed to estimate the constants of COSMO-RS theory and sigma moment model. IFT prediction of representative Omani heavy crude oil in 217 DES in the brine system is reported and analyzed at the mole fraction of DES in brine ranging from 1 × 10-3 to 5 × 10-1 with variation in temperature from 298.15 K to 353.15 K. The highest and the lowest values thus obtained for IFT are 560.8 and 0.2 mN/m. There are 26 DESs capable of reducing IFT by more than 50%, while another 10 DESs show a reduction capability of more than 75%. The optimum concentration of DES to maximize IFT reduction is further analyzed.

Dipole Cooperativity and Polarization Frustration Determine the Secondary Structure Distribution of Short Alanine Peptides in Water.

The physical driving forces for secondary structure preferences of hydrated alanine peptide are investigated with B3LYP-D3(BJ) and the adaptive force matching (AFM) method. The AFM fit to the DFT surface, ALA2022, provides excellent agreement with the nuclear magnetic resonance scalar coupling constants from experiments. In turn, the model is used to gain insight into the physical driving forces behind secondary structure preferences of hydrated peptides. DFT calculations with and without the Conductor-like Screening Model (COSMO) show that the α helix is stabilized by solvent polarization due to dipole cooperativity. The two adjacent amide groups in β strand form a near-planar trapezoid that is not much larger than the size of water molecules. When the finite size of a water molecule is considered, the stabilization from solvent polarization for such a trapezoid is frustrated. Water molecules cannot find orientations to properly stabilize all four polar regions close to each other with such an awkward arrangement. This leads to quite substantial reduction in polarization stabilization. Although the polyproline II (PP-II) conformation is very similar to the β strand, the small twist in the backbone angles allowed much improved polarization stabilization. The improved polarization, when combined with favorable intrapeptide interactions, leads to the PP-II to be lowest in free energy. Other factors, such as the entropic TΔS and the ϕ, ψ coupling terms, are also studied but are found to play only a minor role. The insight shown in this work helps to better understand the structure of globular and intrinsic disordered proteins and facilitate future force field development.

Unveiling the thermodynamic and molecular mechanisms for the separation of diethoxymethane and ethanol azeotrope by deep eutectic solvents

The selection of efficient and environmental extractants is essential for the sustainable development of extraction processes. Based on the conductor-like screening model for the segment activity coefficient (COSMO-SAC), three deep eutectic solvents (DESs) were screened from 1000 DESs for the separation of diethoxymethane (DEM) and ethanol (EA). Subsequently, the liquid–liquid equilibrium behavior of the DEM + EA + DES system at different temperatures was measured. The results show that benzyltrimethylammonium chloride/glycerol (BTACl/GLY) has the highest selectivity and benzyltrimethylammonium chloride/ethylene glycol (BTACl/EG) and tetraethylammonium chloride/ethylene glycol (TEACl/EG) have similar extraction performance. More importantly, the extraction performance of DESs reported in this work is stronger than that of the solvents already reported. Additionally, analysis of the separation mechanism by various quantum chemical methods revealed that the purification of DEM and EA mixtures is mainly ascribed to the difference in electrostatic forces between the solvent and DEM/EA. The result confirmed that solvents with small molecular structures and strong nucleophilic sites are more competitive in separating the mixtures.