Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces

Simulations of chemical reaction probabilities in gas surface dynamics require the calculation of ensemble averages over many tens of thousands of reaction events to predict dynamical observables that can be compared to experiments. At the same time, the energy landscapes need to be accurately mappe...

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Detalhes bibliográficos

Principais autores:	Wojciech G Stark, Cas van der Oord, Ilyes Batatia, Yaolong Zhang, Bin Jiang, Gábor Csányi, Reinhard J Maurer
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IOP Publishing 2024-01-01
coleção:	Machine Learning: Science and Technology
Assuntos:	molecular dynamics simulations electronic structure theory gas surface dynamics machine learning model inference performance reactive scattering hydrogen surface chemistry
Acesso em linha:	https://doi.org/10.1088/2632-2153/ad5f11
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