E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

An E(3)-equivariant deep learning interatomic potential is introduced for accelerating molecular dynamics simulations. The method obtains state-of-the-art accuracy, can faithfully describe dynamics of complex systems with remarkable sample efficiency.

Bibliographic Details
Main Authors: Simon Batzner, Albert Musaelian, Lixin Sun, Mario Geiger, Jonathan P. Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E. Smidt, Boris Kozinsky
Format: Article
Language:English
Published: Nature Portfolio 2022-05-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-022-29939-5