The CATBOOST as a tool to predict the isothermal compressibility of ionic liquids

In this work, we explore the possibility for calculating the isothermal compressibility of Ionic Liquids at atmospheric pressure by combination of the CATBOOST machine learning library and Wada's rule. The CATBOOST predicts the isothermal compressibility at 298.15 K using the density at the same temperature, the critical temperature and pressure, the molar mass, and the acentric factor. The obtained value plays the role of reference one combined with the power-law dependence on the density to get the target compressibility in a wider temperature range. The isothermal compressibilities for 35 Ionic Liquids, given in literature, were used for the comparison and its analysis. The average result at 298.15 K was 6.0% while for the whole range of temperatures was 6.2%. The influence of machine learning parameters on the prediction is discussed. (C) 2021 Elsevier B.V. All rights reserved.