Overview of Activity Coefficient of Thiophene at Infinite Dilution in Ionic Liquids and their Modeling Using COSMO-RS

Abstract

Ionic liquids (ILs) gained a lot of attention, from both academe and industry, as alternative liquids for different types of applications. Chemical and physical characteristics can be designed with the large availability of cation and anions. Experimental measurement of all these systems is not practically feasible, hence requiring the use of a computational predictive model study. This work evaluates the prediction of the activity coefficient (γ s ∞) at infinite dilution in several classes of ILs using the conductor-like screening model for real solvents (COSMO-RS), a model based on unimolecular quantum chemistry calculations. Comparison of the experimental γ s ∞ value with COSMO-RS predicted data is carried out, and absolute average relative deviation was determined to be 24.1%, indicating that the COSMO-RS model presents a reliable prediction to determine γ s ∞ in a wide range of ILs. The observation also confirms that polarizability of ILs plays a crucial role in their interaction with thiophene. With respect to cation impact, it is more evident to state that γ s ∞ decreases with increasing the cation size. The results shown here help in understanding of IL–thiophene interactions. The effect of various structural features of ILs on γ s ∞ can be observed, which aids in the development of various steps for the design of most suitable ILs with improved interaction with thiophene.

Screening of Ionic Liquids for Keratin Dissolution by Means of COSMO-RS and Experimental Verification

“…20 It has also attracted a significant amount of attention in terms of ILs, as it integrates the dominant interaction forces of H-bonds, misfits and van der Waals in ILs systems. [21][22] Many results on the prediction of polymer properties in ILs have been reported, and it is obvious that calculating the activity coefficients, 23 solubility coefficients 1,24 and excess enthalpy 25 of polymer in ILs is an effective way of evaluating the dissolution ability of the ILs. Casas et al, 26 for instance, found that the solubility of cellulose and lignin could be accurately predicted by using activity coefficients and excess enthalpy via COSMO-RS.…”

Computer‐aided design of ionic liquids as solvents for extractive desulfurization

“…As summarized in Table , the MAPE between experimental and UNIFAC‐IL calculated γ ∞ of thiophene for the 405 data points is only 4.42%. In comparison, the MAPE between experimental and COSMO‐RS predicted γ ∞ of thiophene in 52 ILs (325 data points) is 24.10% . Similarly, the corresponding MAPEs in the cases of aromatics, n ‐alkanes, and cycloalkanes are 10.05%, 26.82%, and 32.28%, respectively, which are also much smaller than the ones predicted from COSMO‐RS .…”

An Overview on the Toxicological Properties of Ionic Liquids toward Microorganisms

“…These models include predictive quantitative structure–activity relationship (QSAR) models, molecular docking, structure–activity relationship (SAR) systems, read‐across models, physiology‐based pharmacokinetic models, and quantitative toxicity–toxicity relationship (QTTR) models . In addition to toxicity predictions, these models have been successful in forecasting various physicochemical properties of ILs, such as melting points, surface tensions, infinite dilution activity coefficients, viscosities, conductivities, solubilities, glass transition temperatures, and decomposition temperatures …”

“…These models include predictive quantitative structure-activity relationship (QSAR) models, [42][43][44][45] molecular docking, [46] structure-activity relationship (SAR) systems, [47] read-across models, [48][49][50] physiology-based pharmacokinetic models, [51,52] and quantitative toxicity-toxicity relationship (QTTR) models. [53] In addition to toxicity predictions, these models have been successful in forecasting various physicochemical properties of ILs, such as melting points, [54,55] surface tensions, [56,57] infinite dilution activity coefficients, [58][59][60] viscosities, [61,62] conductivities, [63,64] solubilities, [65,66] glass transition temperatures, [64] and decomposition temperatures. [67] Determining the relationship between toxicity and structural features is one of the most basic processes of a model and this is made possible through computational chemistry.…”