QSPR study on the viscosity of bis(trifluoromethylsulfonyl)imide-based ionic liquids

Viscosity of Ionic Liquids: Theories and Models

Ionic liquids (ILs) offer a wide range of promising applications due to their unique and designable properties compared to conventional solvents. Further development and application of ILs require correlating/predicting their pressure-viscosity-temperature behavior. In this review, we firstly introduce methods for calculation of thermodynamic inputs of viscosity models. Next, we introduce theories, theoretical and semi-empirical models coupling various theories with EoSs or activity coefficient models, and empirical and phenomenological models for viscosity of pure ILs and IL-related mixtures. Our modelling description is followed immediately by model application and performance. Then, we propose simple predictive equations for viscosity of IL-related mixtures and systematically compare performances of the above-mentioned theories and models. In concluding remarks, we recommend robust predictive models for viscosity at atmospheric pressure as well as proper and consistent theories and models for P-η-T behavior. The work that still remains to be done to obtain the desired theories and models for viscosity of ILs and IL-related mixtures is also presented. The present review is structured from pure ILs to IL-related mixtures and aims to summarize and quantitatively discuss the recent advances in theoretical and empirical modelling of viscosity of ILs and IL-related mixtures.

Viscosity models for ionic liquids and their mixtures

Review of principles and limitations of viscosity models for ionic liquids and their mixtures focusing on the use of inappropriate mixing rules for molten salts.

QSPR Modeling of Liquid-liquid Equilibria in Two-phase Systems of Water and Ionic Liquid

The increasing application of new ionic liquids (IL) creates the need of liquid-liquid equilibria data for both miscible and quasi-immiscible systems. In this study, equilibrium concentrations at different temperatures for ionic liquid+water two-phase systems were modeled using a Quantitative-Structure-Property Relationship (QSPR) method. Data on equilibrium concentrations were taken from the ILThermo Ionic Liquids database, curated and used to make models that predict the weight fraction of water in ionic liquid rich phase and ionic liquid in the aqueous phase as two separate properties. The major modeling challenge stems from the fact that each single IL is characterized by several data points, since equilibrium concentrations are temperature dependent. Thus, new approaches for the detection of potential data point outliers, testing set selection, and quality prediction have been developed. Training set comprised equilibrium concentration data for 67 and 68 ILs in case of water in IL and IL in water modeling, respectively. SiRMS, MOLMAPS, Rcdk and Chemaxon descriptors were used to build Random Forest models for both properties. Models were subjected to the Y-scrambling test for robustness assessment. The best models have also been validated using an external test set that is not part of the ILThermo database. A two-phase equilibrium diagram for one of the external test set IL is presented for better visualization of the results and potential derivation of tie lines.

Prediction of the viscosity of imidazolium-based ionic liquids at different temperatures using the quantitative structure property relationship approach

A multilinear relationship between the viscosity and interaction energies using a stepwise model-building approach was applied to generate the correlation model.

Modeling from Theory and Modeling from Data: Complementary or Alternative Approaches? The Case of Ionic Liquids

In the field of ionic liquids (ILs), theory-driven modeling approaches aimed at the best fit for all available data by using a unique, and often nonlinear, model have been widely adopted to develop quantitative structure-property relationship (QSPR) models. In this context, we propose chemoinformatic and chemometric data-driven procedures that lead to QSPR soft models with local validity that are able to predict relevant physicochemical properties of ILs, such as viscosity, density, decomposition temperature, and conductivity. These models, which use readily available and easily interpretable VolSurf+ descriptors, represent an unexploited opportunity for experimentalists to model and predict the physicochemical properties of ILs in industrial R&D design.

Quantum Chemical Methods for the Prediction of Energetic, Physical, and Spectroscopic Properties of Ionic Liquids

The accurate prediction of physicochemical properties of condensed systems is a longstanding goal of theoretical (quantum) chemistry. Ionic liquids comprising entirely of ions provide a unique challenge in this respect due to the diverse chemical nature of available ions and the complex interplay of intermolecular interactions among them, thus resulting in the wide variability of physicochemical properties, such as thermodynamic, transport, and spectroscopic properties. It is well understood that intermolecular forces are directly linked to physicochemical properties of condensed systems, and therefore, an understanding of this relationship would greatly aid in the design and synthesis of functionalized materials with tailored properties for an application at hand. This review aims to give an overview of how electronic structure properties obtained from quantum chemical methods such as interaction/binding energy and its fundamental components, dipole moment, polarizability, and orbital energies, can help shed light on the energetic, physical, and spectroscopic properties of semi-Coulomb systems such as ionic liquids. Particular emphasis is given to the prediction of their thermodynamic, transport, spectroscopic, and solubilizing properties.

Quantitative Structure Activity Relationship of Cinnamaldehyde Compounds against Wood-Decaying Fungi

Cinnamaldehyde, of the genius Cinnamomum, is a major constituent of the bark of the cinnamon tree and possesses broad-spectrum antimicrobial activity. In this study, we used best multiple linear regression (BMLR) to develop quantitative structure activity relationship (QSAR) models for cinnamaldehyde derivatives against wood-decaying fungi Trametes versicolor and Gloeophyllun trabeum. Based on the two optimal QSAR models, we then designed and synthesized two novel cinnamaldehyde compounds. The QSAR models exhibited good correlation coefficients: R²_Tv = 0.910 for Trametes versicolor and R²_Gt = 0.926 for Gloeophyllun trabeum. Small errors between the experimental and calculated values of two designed compounds indicated that these two QSAR models have strong predictability and stability.

A quantitative prediction of the viscosity of ionic liquids using Sσ-profilemolecular descriptors

A QSPR study of ILs using MLR and SVM algorithms based on COSMO-RS molecular descriptors (S_σ-profile).

Quantitative evaluation of myoglobin unfolding in the presence of guanidinium hydrochloride and ionic liquids in solution

The use of ionic liquids in biochemical and biophysical applications has increased dramatically in recent years due to their interesting properties. We report results of a thermodynamic characterization of the chaotrope-induced denaturation of equine myoglobin in two different ionic liquid aqueous environments using a combined absorption/fluorescence spectroscopic approach. Denaturation by guanidinium hydrochloride was monitored by loss of heme absorptivity and limited unfolding structural information was obtained from Förster resonance energy transfer experiments. Results show that myoglobin unfolding is generally unchanged in the presence of ethylmethylimidazolium acetate (EMIAc) in aqueous solution up to 150 mM concentration but is facilitated by butylmethylimidazolium boron tetrafluoride (BMIBF4) in solution. The presence of 150 mM BMIBF4 alone does not induce unfolding but destabilizes the structure as observed by a decrease in threshold denaturant concentration for unfolding and an 80% decrease in the magnitude of ΔGunfolding from 44 kJ/mol in the absence of BMIBF4 to 8 kJ/mol in the presence of 150 mM BMIBF4. Thus, the BMIBF4 significantly destabilizes the myoglobin structure while the EMIAc does not, likely due to differences in anion interaction capabilities. This is confirmed with control studies using NaAc and LiBF4 solutions. EMIAc may be chosen as cosolvent additive with minimal effects on protein structure while BMIBF4 may be used as a supplement in protein folding experiments, potentially allowing access to proteins which have been traditionally difficult to denature as well as designing ionic liquids to match protein characteristics.