The Phase Diagram of a Deep Potential Water Model

TL;DR

This paper develops a Deep Potential model for water that accurately reproduces the potential energy surface and phase diagram across a wide range of conditions, enabling efficient molecular dynamics simulations.

Contribution

It introduces a deep learning-based water model that accurately predicts phase behavior and atomic dynamics, extending the applicability of potential energy surface modeling.

Findings

Accurately reproduces water's phase diagram from low to high temperature and pressure.

Predicts all stable ice polymorphs except for some metastable phases.

Reveals atomic dissociation processes and covalent fluctuations during phase transitions.

Abstract

Using the Deep Potential methodology, we construct a model that reproduces accurately the potential energy surface of the SCAN approximation of density functional theory for water, from low temperature and pressure to about 2400 K and 50 GPa, excluding the vapor stability region. The computational efficiency of the model makes it possible to predict its phase diagram using molecular dynamics. Satisfactory overall agreement with experimental results is obtained. The fluid phases, molecular and ionic, and all the stable ice polymorphs, ordered and disordered, are predicted correctly, with the exception of ice III and XV that are stable in experiments, but metastable in the model. The evolution of the atomic dynamics upon heating, as ice VII transforms first into ice VII$''$ and then into an ionic fluid, reveals that molecular dissociation and breaking of the ice rules coexist with strong covalent fluctuations, explaining why only partial ionization was inferred in experiments.