New Machine Learning Interatomic Potentials Revolutionize Chemistry and Materials Science

Researchers at Los Alamos National Laboratory have created a breakthrough machine learning model, ANI-1xnr, for predicting molecular energies and forces in atoms, revolutionizing chemistry and materials science. This model bridges the gap between classical force fields and quantum mechanics, offering a balance of speed, accuracy, and generality. ANI-1xnr enables efficient large-scale reactive atomistic simulations across diverse chemical systems without the need for constant refitting, showcasing its potential in studying complex chemical reactions and materials. For further details, you can read the full article on elblog.pl: