Entropy of Liquid Water as Predicted by the Two-Phase Thermodynamic Model and Data-Driven Many-Body Potentials.

Abstract

We investigate the entropy of liquid water at ambient conditions using the two-phase thermodynamic (2PT) model, applied to both common pairwise-additive water models and the MB-pol and MB-pol(2023) data-driven many-body potentials. Our simulations demonstrate that the 2PT model yields entropy values in semiquantitative agreement with experimental data when using MB-pol and MB-pol(2023). Additionally, our analyses indicate that the entropy values predicted by pairwise-additive water models may benefit from error compensation between the inherent approximations of the 2PT model and the known limitations of these water models in describing many-body interactions. Despite its approximate nature, the simplicity of the 2PT model makes it a valuable tool for estimating relative entropy changes of liquid water across various environments, especially when combined with water models that provide a consistently robust representation of the structural, thermodynamic, and dynamical properties of liquid water.