Reposted by @maxim-k.bsky.social
Our review paper, led by @maxim-k.bsky.social from Los Alamos National Lab, is now in @amerchemsociety.bsky.social Chemical Reviews! We dive into data-driven chemistry, focusing on quality training data for ML interatomic potentials. A must-read for computational chemistry and materials science!
pubs.acs.org
Data Generation for Machine Learning Interatomic Potentials and Beyond
The field of data-driven chemistry is undergoing an evolution, driven by innovations in machine learning models for predicting molecular properties and behavior. Recent strides in ML-based interatomic...