Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks

Abstract

Accurate microscopic models of amorphous metal–organic frameworks (MOFs) are difficult to create. Machine learning potentials based on data from ab initio molecular dynamics offer a novel way to achieve this goal.