Predicting solubility of molecular liquids using first principles and adaptive force matching.

Abstract

Accurate prediction of solubility is crucial in various fields, including pharmaceuticals, environmental chemistry, and materials science. In this study, we demonstrate the application of Adaptive Force Matching (AFM) to predict the solubility of molecular liquids in water. By developing high-quality force fields using AFM, we accurately compute the free energy of vaporization and hydration, which are essential components for predicting solubility. Our results show that AFM models can reliably predict the solvation free energy of selected small molecules, exhibiting a deviation of <1.3 kJ/mol from experimental references for cyclohexene, isopentane, and n-butanol. Although a slightly larger error is observed for n-octanol, which was developed by borrowing AFM parameters from other molecules, the deviation remains comparable to commonly accepted chemical accuracy. This study highlights the potential of AFM as a powerful tool for predicting solubility, enabling the design and development of new materials and molecules with tailored properties.