Conductor-like Screening Model For Real Solvents Research Articles

COSMO-RS guided screening of ionic liquids for the separation of fluorinated greenhouse gases R-410A: Delving into anion, cation effects, and hydrogen bond dynamics

Reclamation of high-GWP near-azeotropic refrigerant R-410A (50 wt% R-32 (difluoromethane) + 50 wt% R-125 (pentafluoroethane)) can be an effective way to mitigate the greenhouse effect and achieve a circular economy. Efficient ionic liquids (ILs) as extractants needed to be found for the extractive distillation (ED) separation process of R-410A. Given the numerous combinations of cations and anions in ILs, the discovery of an efficient IL via experimental methods proves to be an exceedingly complex task. In this work, the solubilities of R-32, and R-125 in 840 conventional ILs (comprised of 20 cations and 42 anions) were analyzed based on infinite dilution activity coefficient. The absorption mechanisms of R-32 and R-125 in ILs were elucidated by analyzing excess enthalpy (HE), excess Gibbs free energy (GE)) and surface charge density distribution through COSMO-RS (Conductor-like Screening Model for Real Solvents). Results revealed that HE and GE of the mixture formed by R-125 and most ILs surpassed those of R-32, resulting in higher solubility of R-32 in most ILs compared to R-125. Structural changes of anions and cations had a greater effect on the solubility of R-125 in ILs. It is found for the first time that the existence of a strong hydrogen bond donor region in cations/anions generated intense repulsion with the hydrogen atom in R-125. Furthermore, a large area of weak polarity on the surface of cations/anions was difficult to form an effective charge shield with fluorine atoms in R-125, thus inhibiting the dissolution of R-125. Finally based on the identified interaction sites, combined with melting point and viscosity, some novel functional ILs with high selectivity for R-32 + R-125 were designed and determined for actual separation process. These findings significantly enrich the understanding of the solubility mechanism and provide theoretical guidance for designing new ILs for R-410A reclamation.

Insight into the experiment and extraction mechanism for separating carbazole from anthracene oil with quaternary ammonium-based deep eutectic solvents

Carbazole is an irreplaceable basic organic chemical raw material and intermediate in industry. The separation of carbazole from anthracene oil by environmental benign solvents is important but still a challenge in chemical engineering. Deep eutectic solvents (DESs) as a sustainable green separation solvent have been proposed for the separation of carbazole from model anthracene oil. In this research, three quaternary ammonium-based DESs were prepared using ethylene glycol (EG) as hydrogen bond donor and tetrabutylammonium chloride (TBAC), tetrabutylammonium bromide or choline chloride as hydrogen bond acceptors. To explore their extraction performance of carbazole, the conductor-like screeningmodelfor real solvents (COSMO-RS) model was used to predict the activity coefficient at infinite dilution (γ∞) of carbazole in DESs, and the result indicated TBAC:EG (1:2) had the stronger extraction ability for carbazole due to the higher capacity at infinite dilution (C∞) value. Then, the separation performance of these three DESs was evaluated by experiments, and the experimental results were in good agreement with the COSMO-RS prediction results. The TBAC:EG (1:2) was determined as the most promising solvent. Additionally, the extraction conditions of TBAC:EG (1:2) were optimized, and the extraction efficiency, distribution coefficient and selectivity of carbazole could reach up to 85.74%, 30.18 and 66.10%, respectively. Moreover, the TBAC:EG (1:2) could be recycled by using environmentally friendly water as antisolvent. In addition, the separation performance of TBAC:EG (1:2) was also evaluated by real crude anthracene, the carbazole was obtained with purity and yield of 85.32%, 60.27%, respectively. Lastly, the extraction mechanism was elucidated by σ-profiles and interaction energy analysis. Theoretical calculation results showed that the main driving force for the extraction process was the hydrogen bonding ((N–H…Cl) and van der Waals interactions (C–H…O and C–H…π), which corresponding to the blue and green isosurfaces in IGMH analysis. This work presented a novel method for separating carbazole from crude anthracene oil, and will provide an important reference for the separation of other high value-added products from coal tar.

Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples

The extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the highest FF and HMF solubility were prepared. The detailed physicochemical (i.e. density, viscosity, melting point) and structural characterization of new solvents using spectroscopic analysis and density functional theory (DFT) were performed. The most important liquid–liquid extraction parameters, i.e. the type of MDES, pH, temperature, extraction time, and the ratio of MDES to aqueous phase were carefully optimized using Central Composite Design model (CCD). In addition, multistage extraction, MDES regeneration, and reusability were also examined. The obtained results indicate that MDES consisting of menthol, thymol, and FeCl3 in a 1:1:0.5 M ratio could easily extract both FF and HMF from model and real hydrolysates samples with 98.5 and 78.8 % efficiency, respectively. The MDES regeneration studies demonstrated that the extraction efficiency did not change after 15 regeneration cycles. The mechanism of FF and HMF extraction indicates that van der Waals interactions were the main driving force for the extraction process. A great advantage of the proposed method was the possibility to eliminate the tedious centrifugation step for phase separation by using solvents with magnetic properties.

Bio-based molecular imprinted polymers for separation and purification of chlorogenic acid extracted from food waste

Food waste is a profound challenge as 17% of global food production (i.e., 931 million tons) ends up as waste yearly. A cost-effective strategy is the extraction of high-value phenolic acids from food waste, but their downstream purification is challenging owing to their similar chemical nature, high boiling points, and low concentrations in complex mixtures. Herein, we propose separating target phenolics using molecular imprinted polymers. The stability of the monomer-template complex during the synthesis is critical in optimizing the polymer selectivity and performance. COnductor like Screening MOdel for Real Solvents (COSMO-RS) and Hansen Solubility Parameters in Practice (HSPiP) computations were used to screen the interaction of 28 monomers and 13 porogenic solvents with chlorogenic acid as the target molecule. Experiments revealed that itaconic acid, the functional monomer, and tetrahydrofuran (THF), the synthesis solvent, provide the highest reported separation factor. The polymer exhibits superior selectivity towards chlorogenic acid in concentrated solutions of up to 1 mg/mL, and its high sensitivity to various functionalities enables the effective separation of all target phenolic acids. The polymer's performance was evaluated in different extraction solvents, and Fourier transform infrared (FTIR) studies revealed polymer–solvent interaction as the critical factor influencing its performance. The application of the polymer in purifying up to 92% chlorogenic acid from coffee beans and potato peel waste extractives is demonstrated, and its reusability is evaluated. In contrast to the current industrial purification methodology that produces mixtures, the proposed technology provides at least eleven times higher economic value and 95% less carbon emissions based on lab-scale techno-economic analysis.

Computer-aided design of membrane-free batteries using conductor-like screening model for real solvents

The use of renewable energy sources for electricity generation is increasing, and effective energy storage solutions are needed to manage the mismatch between energy production and demand. Redox Flow Batteries (RFBs), particularly Membrane-Free Flow Batteries based on Aqueous Biphasic Systems (ABSs), are a promising technology for stationary energy storage. However, to prevent the crossover of species, the redox-active compounds used in the catholyte and anolyte must be selectively dissolved, which is currently achieved using expensive physical barriers. In this study, an approach was developed to predict the partition coefficient of redox-active compounds in ABSs formed by ionic liquids or polymers, salt, and water using the Conductor-like Screening Model for Real Solvents (COSMO-RS). Experimental data from literature was used to validate the model, resulting in a good correspondence between predicted and experimental data. Furthermore, the method was used to design viologen derivatives and predict their partition coefficients, nine of which were synthesized and validated experimentally. It was found that derivatives containing amine groups have the highest partition coefficients to the salt-rich phase. COSMO-RS proved to be a powerful tool to accelerate the development of advanced biphasic membrane-free flow batteries by designing and finding combinations of redox species with suitable partition coefficients.

Deep eutectic solvents based in situ isolation technique for extractive deterpenation of essential oils

Essential oils, intricate blends of volatile compounds obtained from a variety of sources, play a crucial role in numerous industries. To elevate product quality, deterpenation becomes an indispensable step. This study proposes an in situ isolation technique based on deep eutectic solvents (DESs) for the deterpenation of essential oil. Salient features of relevant compounds were obtained using conductor-like screening model for real solvents (COSMO-RS) and density functional theory (DFT) methods to predict deterpenation performance. Tetrabutylammonium chloride (TBAC) was chosen based on the results of theoretical analysis and experiment to extract hydroxy-terpenoids. COSMO-RS was employed to evaluate the extraction performance at different molar ratios, and then combined with experimental analysis to determine the optimal conditions. The σ-profiles of organic solvents and their interactions with terpene revealed n-hexane to be the best solvent for purifying DES. TBAC and terpenoids were obtained through the re-extraction procedure, with a recovery of 81.8–84.4%.

Extended Conductor-like Polarizable Continuum Solvation Model (CPCM-X) for Semiempirical Methods.

We have developed a new method to accurately account for solvation effects in semiempirical quantum mechanics based on a polarizable continuum model (PCM). The extended conductor-like polarizable continuum model (CPCM-X) incorporates a computationally efficient domain decomposition conductor-like screening model (ddCOSMO) for extended tight binding (xTB) methods and uses a post-processing approach based on established solvation models, like the conductor-like screening model for real solvents (COSMO-RS) and the universal solvent model based on solute electron density (SMD). According to various benchmarks, the approach performs well across a broad range of systems and applications, including hydration free energies, non-aqueous solvation free energies, and large supramolecular association reactions of neutral and charged species. Our method for computing solvation free energies is much more accurate than the current methods in the xtb program package. It improves the accuracy of solvation free energies by up to 40% for larger supramolecular association reactions to match even the accuracy of higher-level DFT-based solvation models like COSMO-RS and SMD while being computationally more than 2 orders of magnitude faster. The proposed method and the underlying ddCOSMO model are readily available for a wide variety of solvents and are accessible in xtb for use in various computational applications.

Natural deep eutectic solvents for the extraction of lentinan from shiitake mushroom: COSMO-RS screening and ANN-GA optimizing conditions

Using natural deep eutectic solvents (NDES) for green extraction of lentinan from shiitake mushroom is a high-efficiency method. However, empirical and trial-and-error methods commonly used to select suitable NDES are unconvincing and time-consuming. Conductor-like screening model for realistic solvation (COSMO-RS) is helpful for the priori design of NDES by predicting the solubility of biomolecules. In this study, 372 NDES were used to evaluate lentinan dissolution capability via COSMO-RS. The results showed that the solvent formed by carnitine (15 wt%), urea (40.8 wt%), and water (44.2 wt%) exhibited the best performance for the extraction of lentinan. In the extraction stage, an artificial neural network coupled with genetic algorithm (ANN-GA) was developed to optimize the extraction conditions and to analyze their interaction effects on lentinan content. Therefore, COSMO-RS and ANN-GA can be used as powerful tools for solvent screening and extraction process optimization, which can be extended to various bioactive substance extraction.

COSMO-RS in prescreening of Natural Eutectic Solvents for phenolic extraction from Teucrium chamaedrys

Natural Eutectic Solvents (NES) are a promising class of environmentally friendly liquids that offer an alternative to conventional organic solvents. To investigate their potential for extracting phenolic compounds from plant materials, we employed the COSMO-RS (COnductor like Screening MOdel for Real Solvents) computational method. Nineteen NES solvents were prepared to determine the most selective and effective solvent for extracting phenolic compounds from Teucrium chamaedrys using both theoretical and experimental evaluation. Screening of extraction efficiency was performed by quantification of individual compounds using ultra-high-performance liquid chromatography with a diode array detector and a triple-quadrupole mass spectrometer (UHPLC-DAD-MS/MS), as well as spectrophotometric assays (total phenolic content, total flavonoid content, and radical scavenging activity). In this paper, we propose a new approach to model NES properties using COSMO-RS. While the majority of previous studies have modeled these solvents as individual or pseudo-component complexes between hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA), we have developed a ternary HBD:HBA:water supramolecular complex model to represent NES solution structures more accurately. This model provides insights into the intermolecular interactions driving the extraction process and predicts extraction efficiencies that agree with experimental data. Two eutectic mixtures (choline chloride:succinic acid in molar ratio 1:1 and 20% of water (w/w) and choline chloride: glycerol in molar ratio 1:1 and 20% of water (w/w)) showed strong affinity towards phenolic compounds. Overall, our findings suggest that the ternary complex model is a more appropriate approach for modeling NES properties.

Ionic liquid-based dispersive liquid–liquid microextraction of succinic acid from aqueous streams: COSMO-RS screening and experimental verification

ABSTRACT In the present investigation, a total of 108 combinations of ionic liquids (ILs) were screened using the conductor-like screening model for real solvents (COSMO-RS) with the aid of six cations and eighteen anions for the extraction of succinic acid (SA) from aqueous streams through dispersive liquid–liquid microextraction (DLLME). Using the screened ILs, an ionic liquid-based DLLME (IL-DLLME) was developed to extract SA and the role of different reaction parameters in the effectiveness of IL-DLLME approach was investigated. COSMO-RS results suggested that, quaternary ammonium and choline cations form effective IL combinations with [OH¯], [F¯], and [SO4 2¯] anions due to hydrogen bonding. In view of these results, one of the screened ILs, tetramethylammonium hydroxide [TMAm][OH] was chosen as the extractant in IL-DLLME process and acetonitrile was adopted as the dispersive solvent. The highest SA removal efficiency of 97.8% was achieved using 25 μL of IL [TMAm][OH] as a carrier and 500 μL of acetonitrile as dispersive solvent. The highest amount of SA was extracted with a stir time of 20 min at 300 rpm, followed by centrifugation for 5 min at 4500 rpm. Overall, the findings showed that IL-DLLME is efficient in extracting succinic acid from aqueous environments while adhering to the first-order kinetics.

Prediction of solvation energies at infinite dilution by the tc-PR cubic equation of state with advanced mixing rule based on COSMO-RS as gE model

The prediction of solvation quantities is an important issue in several fields of chemical and process engineering. In this regard, this work was conducted to increase the prediction power of the equation-of-state (EoS) approach by coupling the tc-PR (translated-consistent Peng-Robinson) EoS with COSMO-RS (Conductor-like Screening Model for Real Solvents) as gE model through an advanced mixing rule. Since the only input parameter of the COSMO-RS model is the charge density (σ) profile of each molecule, the resulting EoS (called tc-PR/COSMO-RS) does not require any binary interaction parameter contrary to other predictive cubic EoS, such as VTPR, PPR78, PSRK, and UMR-PRU. This feature allows the quantification of solvation data of a great number of systems from readily available pure-component properties (critical temperature and pressure, acentric factor and σ -profile). Satisfactory results were obtained for the prediction of solvation Gibbs energy data that were extracted from the extensive CompSol database (the average absolute deviation is 0.30 kcal/mol). The proposed model represents a very flexible alternative for the prediction of solvation data, since it can deal with a large variety of solutes in either a pure or mixed solvent, and for the entire phase diagram (including the supercritical region).

Exploring ionic liquids for formaldehyde separation via computational COSMO-RS screening

Formaldehyde is an emerging human carcinogen from gaseous spark ignition engines and in aqueous stream. In addition to causing leukaemia and nasal cancer, the emissions harm the environment. The present study examined ionic liquids (ILs) as greener alternatives for removing formaldehyde from different sources. Because of its reliability and excellent predicting ability a conductor-like screening model for real solvents (COSMO-RS) were employed as a simulation means to evaluate potential ILs for formaldehyde. Screened IL can be used as an extracting agent, an adsorbent, a carrier, or an absorbent in formaldehyde separation. 392 different cation-anion combinations were screened. To measure the efficacy of IL, the activity coefficient at infinite dilution, capacity, selectivity, and interaction energies were predicted for all 1600 ILs combinations. Short-chain quaternary ammonium cations were found to be potentially effective compared to long-chain and aromatic cations. Moreover, halogenated and food-grade anions such as fluoride, acetate, and lysinate showed higher capacity and selectivity. Whereas than weakly coordinating anions such as [AsF6] and [BCl4] were observed to be least effective for formaldehyde separation. ILs tetramethylammonium hydroxide [TMAmm][OH], tetramethylammonium fluoride [TMAmm][F], tetramethylammonium acetate [TMAmm][Ac], and [TMAmm][Lys] were found to be the most effective separating agents for formaldehyde. This study will facilitate the selection and design of biobased ILs for the separation of formaldehyde.

A Comparison between High-Performance Countercurrent Chromatography and Fast-Centrifugal Partition Chromatography for a One-Step Isolation of Flavonoids from Peanut Hulls Supported by a Conductor like Screening Model for Real Solvents.

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).

Enhanced extraction of brominated flame retardants from e-waste plastics

Acrylonitrile butadiene styrene (ABS) is a high utility engineering thermoplastic, abundantly present in waste electronic and electrical goods. The demand for this plastic resin increases continuously with rapid industrial growth across the world. During the recycling of e-waste plastics, it is a common occurrence to find brominated flame retardants, such as Tetrabromobisphenol A (TBBPA) in the plastic. These flame retardants are intentionally added to the plastics as additives. Three processes were investigated to find the optimum solvent/antisolvent combinations, process parameters for the efficient recovery of TBBPA free plastics: microwave assisted extraction (MAE), ultrasound assisted extraction (UAE), and dissolution reprecipitation (DR). Rigorous solvent screening was carried out for both TBBPA and ABS using Hansen Solubility Parameters (HSP), and their interactions with the solvents were investigated with a molecular based Conductor like Screening Model for Realistic Solvents (COSMO-RS) software platform. A 4:1 (v/v) solvent mixture of 1-propanol and heptane was found to be ideal for the solid–liquid extraction process. The optimal extraction conditions (Temperature = 110 – 130 °C, time = 60 to 70 min solid/liquid ratio of 0.025) in MAE were predicted using machine learning based Support Vector Regression (SVR) technique. MAE was found to be superior to UAE and DR processes in terms of quantity and quality of recovered plastics. The maximum extraction efficiencies for TBBPA removal were achieved with MAE, UAE, and DR processes at 95.81%, 93.92%, and 98.15%, respectively. However, the DR process had a relatively lower plastic recovery.

Predicting the CO2 Capture Capability of Deep Eutectic Solvents and Screening over 1000 of their Combinations Using Machine Learning

Deep eutectic solvents (DESs) are a new class of environmentally friendly solvents that have attracted the attention of many researchers. Since DESs have several practical applications in CO2 capture, knowledge of their CO2 solubility is crucial. In this study, the CO2 solubility of DESs was predicted via a multilayer perceptron (MLP) using molecular descriptors derived from the Conductor-like Screening Model for Real Solvents (COSMO-RS). An extensive database of 2327 data points was created from 94 unique DES mixtures made from 2 anions, 17 cations, and 39 hydrogen bond donors (HBDs) at 150 different compositions and operating conditions of temperatures and pressures. Several statistical tests were performed, and after thorough hyperparameter tuning, it was found that the best MLP architecture predicted the CO2 solubility with an R2 value of 0.986 ± 0.002 and an average absolute relative deviation (AARD) of 4.504 ± 0.507. The MLP has also been loaded into an accessible Excel spreadsheet included in the Supporting Information. Thereafter, in order to guide DES molecular design for achieving high CO2 solubilities, the MLP was utilized for the high-throughput screening of 1320 DES combinations. This model encourages the creation of robust and accurate models to predict the CO2 solubility of novel DESs, which will minimize the need for conducting costly and time-consuming experiments.

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%.

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.

Evaluating ionic liquids for its potential as eco-friendly solvents for naproxen removal from water sources using COSMO-RS: Computational and experimental validation

An emerging contaminant of concern in aqueous streams is naproxen. Due to its poor solubility, non-biodegradability, and pharmaceutically active nature, the separation is challenging. Conventional solvents employed for naproxen are toxic and harmful. Ionic liquids (ILs) have attracted great attention as greener solubilizing and separating agent for various pharmaceuticals. ILs have found extensive usage as solvents in nanotechnological processes involving enzymatic reactions and whole cells. The employment of ILs can enhance the effectiveness and productivity of such bioprocesses. To avoid cumbersome experimental screening, in this study, conductor like screening model for real solvents (COSMO-RS) was used to screen ILs. Thirty anions and eight cations from various families were chosen. Activity coefficient at infinite dilution, capacity, selectivity, performance index, molecular interactions using σ-profiles and interaction energies were used to make predictions about solubility. According to the findings, quaternary ammonium cations, highly electronegative, and food-grade anions will form excellent ionic liquid combinations for solubilizing naproxen and hence will be better separating agents. This research will contribute easy designing of ionic liquid-based separation technologies for naproxen. In different separation technologies, ionic liquids can be employed as extractants, carriers, adsorbents, and absorbents.

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.