Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Electric fields are central to a myriad of natural and technological processes.

In this paper, TYC researchers present a machine learning method that enables molecular dynamics simulations under finite electric fields at length and time scales previously unattainable with traditional first-principles approaches. They demonstrate its effectiveness by applying it to liquid water, achieving excellent agreement with existing experimental and computational results.

Authors: Kit Joll, Philipp Schienbein, Kevin M. Rosso, Jochen Blumberger

DOI: https://doi.org/10.1038/s41467-024-52491-3, 18 September 2024