Check out our new collaborative paper on machine learning for nonadiabatic molecular dynamics published in @chemicalscience.rsc.org. It provides an overview of the current state-of-the-art and best practices. Thx to
@jwestermayr.bsky.social @stevenalopez.bsky.social @rcrespootero.bsky.social ...
doi.org
Machine learning for nonadiabatic molecular dynamics: best practices and recent progress
Exploring molecular excited states holds immense significance across organic chemistry, chemical biology, and materials science. Understanding the photophysical properties of molecular chromophores is...