Conductor-like Screening Model For Real Solvents Research Articles

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.

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.

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.

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.

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.

Extraction of valuable chemicals from food waste via computational solvent screening and experiments

About 1.3 billion tons of global food production end up in landfills and composting, leading to significant anthropogenic greenhouse gas (GHG) emissions. Extracting antioxidant and antimicrobial chemicals (flavonoids, phenolic acids, etc.) from food waste is an economically lucrative valorization strategy but is hindered by efficient solvent selection. Here we perform in silico high throughput screening to identify high solubility solvents for key phenolics and reveal >100+ higher-performing solvents than the traditional ethanol and methanol. Solubilities of nine shortlisted solvents are measured and found in reasonable agreement with model predictions. Analysis of the Conductor like Screening Model for Real Solvents (COSMO-RS) σ-profiles and Hansen Solubility Parameters reveals that polarity and hydrogen bonding make dimethylformamide (DMF) an excellent single solvent. We showcase the replacement of high-solubility toxic solventswith green mixtures and demonstrate the approach to potato peel waste. Our work provides a blueprint for solvent selection and generates new insights into extraction from food waste.

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.