Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential

Abstract

Hydrogen has multiple molecular phases which are challenging to explore computationally. The authors develop a machine-learning approach, learning from reference ab initio molecular dynamics simulations, to derive a transferable hierarchical force model that provides insight into high pressure phases and the melting line of H2.