Machine learning interatomic potentials (MLIPs) have become an essential tool to enable long-time scale simulations of materials and molecules at unprecedented accuracies. The aim of this collection ...

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials ...

Quantum calculations of molecular systems often require extraordinary amounts of computing power; these calculations are typically performed on the world’s largest supercomputers to better understand ...

A simulation demonstrates the reactions that the ANI-1xnr can produce. ANI-1xnr can simulate reactive processes for organic materials, such as as carbon, using less computing power and time than ...