Yuliya A. Fadeeva

Ionic liquids (ILs) and deep eutectic solvents (DESs) have been extensively studied as absorbents for CO₂ capture, demonstrating high efficiency in this role. To optimize the search for compounds with superior absorption properties, theoretical approaches, including machine learning methods, are highly relevant. In this study, machine learning models were developed and applied to predict Henry’s law constants for CO₂ in ILs and DESs, aiming to identify systems with the best absorption performance. The accuracy of the models was assessed in interpolation tasks within the training set and extrapolation beyond its domain. The optimal predictive models were built using the CatBoost algorithm, leveraging CDK molecular descriptors for ILs and RDKit descriptors for DESs. To define the applicability domain of the models, the SHAP-based leverage method was employed, providing a quantitative characterization of the descriptor space where predictions remain reliable. The developed models have been integrated into the web platform chem-predictor, where they can be utilized for predicting absorption properties.

In this study, new proton conducting membranes were prepared using poly-2,2'-(m-phenylene)-5,5'-bibenzimidazole (PBI) and varying amounts of methylimidazoliumtriflate[MeIm/TfO], a protic ionic liquid, by the solution casting method. The thermal properties and conductivity of these membranes were investigated. The obtained parameters, such as high thermal stability (235–255°C) and the conductivity of 0.7–1.6 mS/cm at 145°C, indicate that PBI membranes doped with either MeIm/TfO or BuIm/TfO, which were previously studied by our group, are quite interesting for further investigation as potential electrolytes for PEMFCs.

Due to the increasing global demand for sustainable energy sources, fuel cells are being considered as a green alternative to conventional power generation methods. Proton Exchange Membrane Fuel Cells (PEMFCs) are particularly promising energy sources due to their high energy efficiency and low environmental impact. However, there is an urgent need to develop proton-conducting materials that can operate under low-humidity conditions and at high working temperatures. In this study, new proton conducting membranes were prepared using poly-2,2'-(m-phenylene)-5,5'-bibenzimidazole (PBI) and varying amounts of a protic ionic liquid, methylimidazolium triflate [MeIm/TfO], through a solution casting method. The thermal properties and conductivity of these membranes were investigated. The obtained parameters indicate that PBI membranes doped with either MeIm/TfO or BuIm/TfO, which were previously studied by our group, are of definite interest for further investigation as potential electrolytes for PEMFCs.

We focus on a series of protic ionic liquids (PILs) with imidazolium and alkylimidazolium (1R3HIm, R=methyl, ethyl, propyl, and butyl) cations. Using the literature data and our experimental results on the thermal and transport properties, we analyze the effects of the anion nature and the alkyl radical length in the cation structure on the above properties. DFT calculations in gas and solvent phase provide further microscopic insights into the structure and cation‐anion binding in these PILs. We show that the higher thermodynamic stability of an ion pair raises the PIL decomposition temperature. The melting points of the salts with the same cation decrease as the hydrocarbon radical in the cation becomes longer, which correlates with the weaker ion‐ion interaction inthe ion pairs. A comparative analysis of the protic ILs and corresponding ILs (1R3MeIm) with the same radical (R) in the cation structure and the same anion has been performed. The lower melting points of the ILs with 1R3MeIm cations are assumed to result from the weakening of both the ion‐ion interaction and the hydrogen bond.