Realistic phase diagram of water from "first principles" data-driven quantum simulations

15 May 2023, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


Since the experimental characterization of the low-pressure region of the phase diagram of water in the early 1900s, scientists have been on a quest to understand the thermodynamic stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from “first principles” and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, which correctly describe the quantum nature of molecular motion and thermodynamic equilibria, enables computer simulations of the phase diagram of water with an unprecedented level of realism. Besides providing unique insights into how enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water, we demonstrate that recent progress in data-driven many-body potentials and simulation algorithms has effectively opened the door to realistic computational studies of complex molecular systems, thus bridging the gap between experiments and simulations.


phase diagram
many-body interactions
machine learning
quantum effects
enhanced sampling
molecular dynamics
path-integral molecular dynamics

Supplementary materials

Supplementary Information
Theoretical methods, computational algorithms, and simulation details. Additional analyses.


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