Conductor-like Screening Model Research Articles

Ultrasonic-Assisted Extraction of Toxic Acidic Components from Acidic Oil Using 1,8-Diazobicyclo[5.4.0]undec-7-ene-Based Ionic Liquids.

Ionic liquids (ILs) show remarkable performance in enhancing the naphthenic acid extraction efficiency and decreasing the extraction time. However, the ultrasonic-assisted IL-based extraction of naphthenic acid is merely addressed previously. Therefore, this study investigated the impact of essential ultrasonic parameters, including amplitude and time, on naphthenic acid extraction using different ILs, and the system was optimized for maximum extraction. The IL 1,8-diazobicyclo[5.4.0]-undec-7-ene (DBU) with thiocyanate anions revealed the highest efficiency in extracting naphthenic acid from a model oil (dodecane) at optimized conditions, and the experimental liquid–liquid equilibrium data were obtained at atmospheric pressure for the mixture of dodecane, [DBU], thiocyanate, and naphthenic acid. In addition, the influence of the chain length of the cation (hexyl, octyl, or decyl) on the extraction efficiency was also evaluated by determining the distribution coefficients, and the conductor-like screening model for real solvents (COSMO-RS) study was carried out at infinite dilution. It was found that [DBU-Dec] [SCN] gives the best extraction efficiency and has a distribution coefficient of 9.2707 and a performance index of 49.48. Based on these values, ILs can be ordered as follows: [DBU-Dec] [SCN] > [DBU-Oct][SCN] > [DBU-Hex][SCN] in the decreasing order of performance index 49.48, 41.58, and 28.13. Moreover, non-random two liquid and Margules thermodynamic models were employed to investigate the interaction parameters between the components. Both models showed excellent agreement with the experimental results and could successfully be used for ultrasonic-assisted IL extraction of naphthenic acid.

Performance evaluation and molecular dynamics simulation in the Liquid–liquid extraction process of low transition temperature mixture + n-hexane + 1,2-Dichloroethane

Vinyl sulphate, a new battery additive, can significantly improve battery performance, but its production process generates a large amount of n-hexane + 1,2-dichloroethane (DCE) azeotropic mixtures. In this paper, green and efficient Low Transition Temperature Mixtures (LTTMs) were used as solvents to explore their separation performance and mechanism of the n-hexane + DCE azeotrope system. Firstly, the conductor-like screening model for segment activity coefficient (COSMO-SAC) model was used to investigate the effects of the structure and composition of the hydrogen bond donors and hydrogen bond acceptors on the extraction performance. On this basis, three LTTMs were screened out as solvents for the extraction and separation of n-hexane + DCE by combining experiments, which were trimethylamine hydrochloride-levulinic acid 1:2 (LTTM1), tetraethylammonium chloride-levulinic acid 1:2 (LTTM2), tetraethylammonium chloride-pyruvic acid 1:2 (LTTM3). Afterward, Liquid–liquid equilibrium (LLE) experiments were carried out for the ternary system of n-hexane + DCE + LTTMs, and the results showed that the extraction of DCE was favored by low temperatures in the experimental temperature range. Then, molecular dynamics simulation was used to investigate the microscopic mechanism of the extraction and separation of n-hexane + DCE by LTTMs. The results showed that the interaction between LTTMs and DCE was much larger than that between LTTMs and n-hexane, n-hexane and DCE, which was the fundamental reason for the separation of n-hexane + DCE by LTTMs. Finally, the continuous separation process of n-hexane + DCE was simulated using Aspen Plus, and the results showed that LTTMs had good extraction performance and the purity of n-hexane and DCE products could reach 99.6 mol% and 99.5 mol%, respectively. The feasibility and microscopic mechanism of the extraction and separation of n-hexane + DCE by LTTMs were investigated using a combination of experiments and simulations, which provided a methodological reference for the separation of n-hexane + DCE.

Highly efficient separation of benzene + cyclohexane mixtures by extraction combined extractive distillation using imidazolium-based dicationic ionic liquids

Benzene (BEN) and cyclohexane (CYH), which have very close boiling points and a binary azeotrope, are the most difficult binary components in the separation of aromatic and non-aromatic hydrocarbons. This study further explored the separation mechanism and industrial application prospects of BEN ​+ ​CYH mixtures separated by a dicationic ionic liquid (DIL) [C5(MIM)2][NTf2]2 based on experimental research. The calculation results of the Conductor-like Screening model Segment Activity Coefficient (COSMO-SAC) model show that selectivity and solvent capacity of the DIL are significantly improved. The effects of different anions and cations on the microstructure distribution and diffusion behavior of BEN ​+ ​CYH system were investigated by quantum chemistry (QC) calculations and molecular dynamics (MD) simulations. The results indicate that the anion [NTf2]− has low polarity, uniform charge distribution, and a dual role of hydrogen bonding and π-π bonding, and the cation [C5(MIM)2]2+ has stronger interaction with BEN and higher selectivity than conventional cations. The liquid-liquid extraction and extractive distillation (LLE-ED) process using an optimized 65 mol/mol DIL ​+ ​35 mol/mol H2O mixed solution as the extractant was proposed, which solved the problem of low product purity in the LLE process and high energy consumption in the ED process. Under the best operating conditions, the purity of CYH product was 99.9%, the purity of BEN product was 99.6%, the recovery rate of BEN reached 99.9%, and the recovery rate of DIL reached 99.9%. The heat-integrated LLE-ED process reduced total annual cost by 21.6%, and reduced CO2 emissions by 48.0%, which has broad industrial application prospects.

Using COSMO-RS to Predict Hansen Solubility Parameters

Hansen solubility parameters (HSP) provide essential information on the nature of solvents, being a useful tool in their selection for product and process design. In this work, linear models were developed to estimate HSP based on the use of COSMO-RS (conductor-like screening model for realistic solvents) descriptors. Hansen solubility parameters for 195 compounds were obtained from the literature and classified into two categories: training set (133 compounds) and testing set (62 compounds). Then a factorial regression was carried out to predict dispersion, hydrogen-bonding interaction, and polar contribution of HSP (δD, δH, and δP, respectively) based on σ-moments and energy COSMO-RS descriptors. The description of the dispersion contribution was the least successful due to the low variability of the experimental data, despite the database containing compounds of a widely different chemical nature. The models obtained proved to be more than simple mathematical equations since a physical meaning is achieved when COSMO-RS descriptors are used. The models developed were then applied to the test database. An excellent performance was observed, with δH showing the highest R2 (0.90), and the MAE obtained were 0.98, 1.74, and 1.44 MPa1/2 for δD, δH, and δP, respectively, which are lower than those found in previous works. Finally, HSP data for caffeine, nicotine, paracetamol, and d-camphor were estimated. The results were close to the literature data and those predictive by the HSPiP software. Moreover, it was shown that δP and δH drive the molecules’ polarity, impacting their log Kow (a quantitative measure of polarity). This work shows that COSMO-RS descriptors are a tool to predict HSP through linear models, opening new doors in the screening, design, and selection of solvents to be used in chemical processes.

Deep removal of chlorobenzene based volatile organic compounds from exhaust gas with ionic liquids

Taking chlorobenzene (C6H5Cl) and o-dichlorobenzene (C6H4Cl2) as representatives of chlorobenzene based volatile organic compounds (CBs), a novel deep-purification technology of absorbing with ionic liquids (ILs) as absorbent was proposed and systematically investigated. Based on conductor-like screening model for real solvents (COSMO-RS) model, the suitable IL 1-ethyl-3-methylimidazolium tetrafluoroborate ([EMIM][BF4]) for absorbing CBs was screened out from 289 kinds of commonly used ILs. Removal experiments of C6H5Cl and C6H4Cl2 by [EMIM][BF4] were carried out at different temperatures, pressures and IL flow rates. Results suggested that [EMIM][BF4] had excellent absorption properties, and deep removal of CBs can be achieved that the content of C6H5Cl/C6H4Cl2 in the purified gas can be decreased down to 13.6 ppm/9.9 ppm (in molar fraction). Absorption capacity of [EMIM][BF4] to CBs was almost unchanged after absorbing and desorbing for up to 20 times, proving the repeatability of the absorption performance. Characterization by NMR and FT-IR showed that there was no chemical bond formed between [EMIM][BF4] and CBs, proving that the absorption process was physical absorption. Moreover, the structure of the regenerated [EMIM][BF4] had not been changed, which indicates that [EMIM][BF4] has strong thermal stability and chemical stability. Finally, the interaction mechanisms between [EMIM][BF4] and CBs were clarified from the aspects of interaction energy and interaction sites by quantum chemical calculation and wave function analysis. This work fills the gap of removing CBs by absorption method with ILs, and proved that ILs could be employed as promising green solvents for chlorobenzene based VOCs removal.

Soybean oil extraction using ethyl acetate and 1-butanol: From solvent selection to thermodynamic assessment

Soybean oil extraction using two green solvents was investigated from solvent selection to thermodynamics: ethyl acetate and 1-butanol. The screening of the solvents was performed using the Hansen parameters and Infinite Dilution Activity Coefficient (IDAC) obtained through the COnductor-like Screening MOdels – Segment Activity Coefficient (COSMO-SAC) theory. The solvent selection was performed on ethyl acetate and 1-butanol in comparison with ethanol, a well-studied green solvent, and hexane, a non-renewable and industrially used solvent. The effects of temperature and solvent/solid ratio on the yield of soybean oil extraction were investigated through response surface methodology (RSM). The RSM obtained satisfactory statistical results, with Radj2 of 0.9958 for ethyl acetate and 0.9729 for 1-butanol. The kinetic of the extractions were evaluated using two different models: mass transfer kinetic and So and Macdonald. The last one obtained the best correlation to the data (R2 > 0.9964). The thermodynamic assessment showed endothermic, and spontaneous processes for both solvents. 1-Butanol, ethyl acetate, and hexane have a better performance on the yield of soybean oil extraction than using ethanol; however, ethyl acetate is the best candidate to replace the industrial use of hexane due to its highest rate of soybean oil extraction at the process beginning.

An open source COSMO-RS implementation and parameterization supporting the efficient implementation of multiple segment descriptors

The model COSMO-RS (Conductor-like screening model for realistic solvation) is based on the approximation of molecular interactions by the interactions of surface segments from the molecular cavities. These segment interactions are functions of the segment properties i.e. descriptors, with the most important descriptor being the screening charge density. Whereas the inclusion of further descriptors can lead to improved accuracy for the models predictions, it also increases the computational demand due to the growth of the central nonlinear equation system of COSMO-RS. In this work, we present an algorithm that efficiently allows the introduction of further segment descriptors at moderate size increase of the central equation system. It is included into our implementation of COSMO-RS, which is provided as open source code and will be named openCOSMO-RS in the future. Different parameterizations of the model are performed, implementing an RDKit/ORCA based workflow for the required quantum chemical calculations. In this way, the implementation is open for evaluation and refinement for a large range of academic users.

Searching for Sustainable Refrigerants by Bridging Molecular Modeling with Machine Learning.

We present here a novel integrated approach employing machine learning algorithms for predicting thermophysical properties of fluids. The approach allows obtaining molecular parameters to be used in the polar soft-statistical associating fluid theory (SAFT) equation of state using molecular descriptors obtained from the conductor-like screening model for real solvents (COSMO-RS). The procedure is used for modeling 18 refrigerants including hydrofluorocarbons, hydrofluoroolefins, and hydrochlorofluoroolefins. The training dataset included six inputs obtained from COSMO-RS and five outputs from polar soft-SAFT parameters, with the accurate algorithm training ensured by its high statistical accuracy. The predicted molecular parameters were used in polar soft-SAFT for evaluating the thermophysical properties of the refrigerants such as density, vapor pressure, heat capacity, enthalpy of vaporization, and speed of sound. Predictions provided a good level of accuracy (AADs = 1.3–10.5%) compared to experimental data, and within a similar level of accuracy using parameters obtained from standard fitting procedures. Moreover, the predicted parameters provided a comparable level of predictive accuracy to parameters obtained from standard procedure when extended to modeling selected binary mixtures. The proposed approach enables bridging the gap in the data of thermodynamic properties of low global warming potential refrigerants, which hinders their technical evaluation and hence their final application.

Strength Enhancement of Regenerated Cellulose Fibers by Adjustment of Hydrogen Bond Distribution in Ionic Liquid.

To improve the physical strength of regenerated cellulose fibers, cellulose dissolution was analyzed with a conductor-like screening model for real solvents in which 1-allyl-3-methylimidazolium chloride (AMIMCl) worked only as a hydrogen bond acceptor while dissolving the cellulose. This process could be promoted by the addition of urea, glycerol, and choline chloride. The dissolution and regeneration of cellulose was achieved through dry-jet and wet-spinning. The results demonstrated that the addition of hydrogen bond donors and acceptors either on their own or in combination can enhance the tensile strength, but their effects on the crystallinity of the regenerated fibers were quite limited. Compared with the regenerated fibers without any additives, the tensile strength was improved from 54.43 MPa to 139.62 MPa after introducing the choline chloride and glycerol, while related the crystallinity was only changed from 60.06% to 62.97%. By contrast, a more compact structure and fewer pores on the fiber surface were identified in samples with additives along with well-preserved cellulose frameworks. Besides, it should be noted that an optimization in the overall thermal stability was obtained in samples with additives. The significant effect of regenerated cellulose with the addition of glycerol was attributed to the reduction of cellulose damage by slowing down the dissolution and cross-linking in the cellulose viscose. The enhancement of the physical strength of regenerated cellulose fiber can be realized by the appropriate adjustment of the hydrogen bond distribution in the ionic liquid system with additives.

Removal of Perfluorooctanoic Acid from Water Using a Hydrophobic Ionic Liquid Selected Using the Conductor-like Screening Model for Realistic Solvents.

The conductor-like screening model for realistic solvents was used to identify ionic liquids (ILs) to efficiently extract perfluorooctanoic acid (PFOA). The infinite dilution chemical potentials of PFOA in 14 000 ILs were calculated and used as descriptors of the chemical affinities between the ILs and PFOA. Trihexyltetradecylphosphonium pivalate ([P6,6,6,14][Piv]) was found to be a good IL for extracting PFOA because it gave a well-balanced combination of a strong chemical attraction for PFOA and useful physicochemical properties. The results of experiments indicated that [P6,6,6,14][Piv] could remove >99.9% of the PFOA in an aqueous solution. However, problematic emulsification of IL in the aqueous phase occurred at PFOA/IL molar ratios <1.9-2.1, and this limited the PFOA removal rate to 80-91%. The ability of the used IL to extract PFOA was found to be partially regenerated by washing the IL with 1% NaOH, and the IL could be reused to extract PFOA with a removal rate decreased by ∼10% in each cycle.

Prediction of acid pKa values in the solvent acetone based on COSMO-RS.

In this contribution we extent the use of the conductor-like screening model for realistic solvation (COSMO-RS) to the prediction of pKa values in acetone, a commonly used dipolar aprotic solvent. For this, we calculated the Gibbs free energy of dissociation of 120 organic acids (nine acrylic acids, 87 benzoic acids, nine phenols, and 15 benzenesulfonamides) using COSMO-RS at the two levels BP-TZVP and BP-TZVPD-FINE and determined the parameters for a linear free energy relation for the prediction by performing linear fits to experimental values. Our results suggest that the data set dissects into two groups, with the phenols being different from the other three subsets. The acrylic and benzoic acids and the sulfonamides can be treated together and yield an excellent linear correlation ( ) with an RMSD of only ~0.3. The slope is found to be significantly smaller than the theoretical value ( ), only 45% of it, which is in accordance with findings in the literature. The phenols, however, while similarly well correlated in their own subset with an RMSD of 1.7-1.9, exhibit a slope larger than one. We discuss both a higher uncertainty in the reference values as well as physical origins as possible reasons.

Ab initio development of generalized Lennard-Jones (Mie) force fields for predictions of thermodynamic properties in advanced molecular-based SAFT equations of state.

A methodology for obtaining molecular parameters of a modified statistical associating fluid theory for variable-range interactions of Mie form (SAFT-VR Mie) equation of state (EoS) from ab initio calculations is proposed for non-associative species that can be modeled as single spherical segments. The methodology provides a strategy to map interatomic or intermolecular potentials obtained from ab initio quantum-chemistry calculations to the corresponding Mie potentials that can be used within the SAFT-VR Mie EoS. The inclusion of corrections for quantum and many-body effects allows for an excellent, fully predictive description of the vapor-liquid envelope and other bulk thermodynamic properties of noble gases; this description is of similar or superior quality to that obtained using SAFT-VR Mie with parameters regressed in the traditional way using experimental thermodynamic-property data. The methodology is extended to an anisotropic species, methane, where similar levels of accuracy are obtained. The efficacy of using less-accurate quantum-chemistry methods in this methodology is explored, showing that these methods do not provide satisfactory results, although we note that the description is nevertheless substantially better than those obtained using the conductor-like screening model for describing real solvents (COSMO-RS), the only other fully predictive ab initio method currently available. Overall, the reliance on thermophysical data is completely dispensed with, providing the first extensible, wholly predictive SAFT-type EoSs.

Theoretical and experimental comparison of rare earths extraction by [P6,6,6,1,4][Decanoate] bifunctional ionic liquid and D2EHPA acidic extractant

The extraction behavior of two lanthanides (La3+ and Y3+) in the nitric acid solution was studied using a bifunctional ionic liquid, namely Trihexyl-tetradecyl-phosphonium Decanoate ([P6,6,6,1,4] [Decanoate]). On comparative study on D2EHPA as a molecular extractant, the ionic liquid revealed remarkably higher extraction capacity of the total are earth elements. The ionic liquid had a separation factor for La/Y smaller than that of the molecular extractant. A high yttrium extraction with an efficiency of > 99% was observed for both extractants, even in low concentrations. The highest efficiency of D2EHPA (20%) equaled 75.04% in the extraction of lanthanum, while this magnitude was > 99% for lanthanum extraction by the ionic liquid. In this study, the Density Functional Theory (DFT) connected to Born Haber Thermodynamics was used along with the solvent effect, imported by the Conductor-like Screening Model (COSMO), for confirming and interpreting the selectivity results, which were observed in the laboratory during the extraction of lanthanum and yttrium. Calculation of the difference in the energy levels of the molecular orbitals of [P6,6,6,1,4] [Decanoate] in the extraction of the neutral complexes of [La.(NO3)3. (H2O)3] ΔEorbital = 0.16 eV) and [Y.(NO3)3. (H2O)2] (ΔEorbital = 0.17 eV) with the neutral or ion pair exchange has shown that this ionic liquid was more efficient than D2EHPA with a cation exchange mechanism in the extraction of the ionic complexes of these elements.

Theoretical study of a single-walled carbon nanotube and a cellulose biofiber as 5-fluorouracil anti-cancer drug carriers

Chemotherapy is one of the most valuable and widely available option in cancer treatment. However, a method of delivering the drug to achieve a therapeutic effect still a considerable challenge. Therefore, this study seeks to identify the non-bonding interaction of 5-fluorouracil anticancer drug with a single walled carbon nanotube and a Cellulose bio-fiber using density functional theory and molecular mechanics simulations. To do that, adsorption locator and DMol3 modules were utilized to determine the electronic and optical properties of carriers before and after adsorption processes. The interaction energies indicate that the 5-fluorouracil molecule can physically adsorb and the optimized geometries are stable. The charge transfer occurs between N4-H10 bond of the 5-fluorouracil molecule and the cellulose carrier by a synergistic effect of hydrogen bond formation and van der Waals forces. This effect smoothly transforms into van der Waals interactions by O3, N4, and N5 atoms in the case of single-walled carbon nanotubes. There is a clear difference in the absorption peak and a significant narrowing of the molecular energy gap of a cellulose complex because of the shifting of the electron accepting center to a drug molecule. The conductor-like screening model shows the affinity of the complexes toward hydrogen bond acceptor, which enhances their solubility in biological systems. A remarkable influence in the case of the cellulose complex works as a starting point to use natural polymers as drug delivery carriers.

Investigation of green solvents for the extraction of phenol and natural alkaloids: Solvent and extractant selection

Green solvents have been gaining momentum to replace traditional volatile organic compounds (VOCs) in solvent extraction processes due to environmental and health concerns. In this work, phenol was used as a model compound for natural alkaloid extraction to find an appropriate alternative among green bio-derived solvents, including d-limonene, α-pinene, p-cymene, 2,5-dimethylfuran (DMF) and CyreneTM. Moreover, extractants including Cyanex 923®, trioctylphosphine oxide (TOPO), tri-butyl-phosphate (TBP) and Alamine 336 were evaluated to investigate the improvement to phenol extraction performance. The selection of extractants and green solvents is based on an evaluation matrix composing several criteria including toxicity, biodegradability, feedstock, market price, physicochemical properties and extraction performance. Hansen solubility parameters (HSPs) and conductor-like screening model (COSMO-SAC) with direction character of hydrogen bonding parameters (DHB) were used to assist the selection process. The COSMO predictions are in good agreement with the experimental data and within 20% deviation in most cases. Finally, d-limonene and Cyanex 923® were selected as the solvent replacement and extractant, respectively. 0.2 M and 0.6 M Cyanex 923® in d-limonene and xylene were further investigated via phenol and morphine isotherms at optimised pH values. It was found that d-limonene exhibits acceptable extraction performance for phenol extraction but is less efficient for morphine extraction as compared to xylene possibly due to emulsion formation during alkaloid extraction.

Carbon Dioxide Solubility in Nonionic Deep Eutectic Solvents Containing Phenolic Alcohols.

Deep eutectic solvents (DES) are a new class of green solvents that have shown unique properties in several process applications. This study evaluates nonionic DES containing phenolic alcohols as solvents for carbon dioxide (CO2) capture applications. Potential phenolic alcohols and the molar ratio between DES constituents were preselected for experimental investigations based on the conductor-like screening model for realistic solvation (COSMO-RS). CO2 solubility was experimentally determined in two different DES, namely, L-menthol/thymol in 1:2 molar ratio and thymol/2,6-xylenol in 1:1 molar ratio, at various temperatures and pressures. CO2 solubility in the studied systems was higher than that reported in the literature for ionic DES and ionic liquids. This study demonstrates that nonionic DES containing phenolic alcohols can be excellent, inexpensive, and simple solvents for CO2 capture.

Systematic method of screening deep eutectic solvents as extractive solvents for m-cresol/cumene separation

Deep eutectic solvents (DESs) have been widely applied as extractive solvents for the separation of phenolic compounds from low-temperature coal tar (LTCT). However, systematic study of screening suitable DESs from numerous candidates for this separation process is still scarce. In this work, a systematic method of screening promising DESs as extractive solvents is proposed for the separation of m-cresol/cumene, as a representative phenolic compound/neutral oil mixture in LTCT. Experimental data of DES-involved systems are collected from literature to validate the reliability of conductor-like screening model for real solvents (COSMO-RS), which serves as the foundation for thermodynamic calculation and process simulation. Then, the crucial influencing factors for DESs screening (i.e., salt and solvent, and the molar ratio) on the thermodynamic properties are investigated by COSMO-RS. After that, a systematic DESs screening method combining the calculation of infinite dilution thermodynamic properties, the estimation of melting point and viscosity, the calculation of liquid-liquid equilibria, and the evaluation of process performance is proposed. The results indicate that chlorocholine chloride (CChC): acetic acid (AA) (1:2) and choline chloride (ChCl): ethylene glycol (EG) (1:3) are identified as the optimum DESs for m-cresol/cumene separation. Finally, the high separation performances of CChC:AA (1:2) and ChCl:EG (1:3) are confirmed by extraction experiments.

Multitask Quantum Study of the Curcumin-Based Complex Physicochemical and Biological Properties.

Density functional theory (DFT), time-dependent density functional theory (TDDFT), quantum theory of atoms in molecules (QTAIM), and extended transition state natural orbitals for chemical valence (ETS-NOCV) have all been used to investigate the physicochemical and biological properties of curcumin and three complexes, i.e., Cur-M (M = Ni, Cu, and Mg). Based on DFT calculations, the enolic form (Cur-Enol) is more stable than the anti-diketone form (Cur-Anti diketone) favored for complexation. This enolic form stability was explained by the presence of three intramolecular hydrogen bonds according to the QTAIM analysis. Furthermore, the ETS-NOCV technique revealed that the enolic form had more significant antioxidant activity compared with the anti-diketone form. The calculations from the COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) showed that the dimethyl sulfoxide (DMSO) solvent could dissolve all the curcumin tautomers Cur-Enol, Cur-Anti-diketone and Cur-Cu, Cur-Mg, and Cur-Ni complexes in contrast to benzene, acetone, octanol, ethanol, methanol, and water. Furthermore, except for Cur-Mg, which had a relatively low solubility (14 g/L), all complexes were insoluble in water. Cur-Anti-diketone was considerably more soluble than Cur-Enol in the examined solvents.

Amino Acid Ionic Liquids as a Potential Adjuvant for Fungicide Formulations: COSMO-RS Prediction and Dissolution Mechanism Elucidation

Screening green solvents to improve the solubility of insoluble pesticides in water is a significant development direction for pesticide formulations in the future. Amino acid ionic liquids (AAILs) have strong dissolution properties and are widely used in dissolution. In this work, the conductor-like screening model for real solvents (COSMO-RS) as a solvent screening tool was used to screen AAILs with good solubility for two insoluble fungicides (fludioxonil and cyprodinil) and the physicochemical properties (viscosity, density, and CMC) of AAILs were characterized. The results showed that the selected AAILs had good solubility effects on fungicides, wherein the solubility of fludioxonil and cyprodinil in 1-ethyl-1-methyl-pyrrolidinium glycinate ([Empy][Gly]) was 115.78 and 67.17 g/L, respectively. The mechanism of the AAIL dissolving the fungicide was explored by theoretical calculation and IR characterization, indicating that the hydrogen bond interaction was the main driving force for AAILs to dissolve fungicides. The solubilization effects of AAILs in different systems were explored, and the results showed that the solubilization effect in aqueous solution was positively correlated with the content of AAILs, which was not only related to the interaction between fungicides and AAILs, but also the formation of micelles as an essential factor. Moreover, the impact of the biosurfactant rhamnolipid (Rha) and AAILs on the solubilization effect was explored, and most AAILs demonstrated a synergistic solubilization effect after adding Rha, which was expected. Finally, the inhibitory effects of organic solvent adjuvant methanol and eight AAILs on wheat growth were measured. Three [Empy] ILs showed less inhibitory effects on wheat than methanol under the same concentration. The research results indicated that AAILs had a promising research prospect as cosolvents in pesticide formulations.

Solubility determination and prediction for FOX-7 in three binary solvents at different temperatures

ABSTRACT The solid–liquid equilibrium and thermodynamic properties of FOX-7 in three binary mixed solvents (N-methyl pyrrolidone-water, N,N-dimethylacetamide-water and 1,4-Butyrolactone-water) are studied by focused beam reflectance measurement (FBRM) dynamic detection method and the solubility is predicted by conductor-like screening model for real solvents (COSMO-RS) under atmospheric pressure from 298.15 to 343.15 K. The results show that the solubility of FOX-7 increase with the increasing temperature and the mole fraction of N-methyl pyrrolidone, N,N-dimethylacetamide and 1,4-Butyrolactone. The solubility data can be well correlated by Apelblat, van’t Hoff and Yaws equation. The data of hybrid thermodynamic parameters (including the hybrid enthalpy, entropy, and Gibbs energy) show that the dissolution process is endothermic, non-spontaneous and enthalpy driven. In addition, COSMO-RS can accurately predict the increasing trend of solubility with increasing of temperature and mole fraction of solvent. However, the COSMO-RS overestimates solubility in three binary solvents except for x NMP = 0.1575, the average mean squared quadratic error becomes larger with an increasing mole fraction of water. Solubility data and thermodynamic parameters can lay a foundation for the crystallization and spheroidization modification of FOX-7.