Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks
Nicolas Castel, Dune André, Connor Edwards, Jack D. Evans, François‐Xavier Coudert
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.
Topics & Concepts
Zeolitic imidazolate frameworkAmorphous solidImidazolateMaterials scienceNanotechnologyChemical physicsComputer scienceChemical engineeringChemistryCrystallographyPhysical chemistryEngineeringMetal-organic frameworkAdsorptionMachine Learning in Materials ScienceX-ray Diffraction in CrystallographyAdvanced Memory and Neural Computing