Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surf...
Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces
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Publisher
Bristol: IOP Publishing
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Language
English
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Publisher
Bristol: IOP Publishing
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Contents
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 mapped, as small errors in barriers can lead to large d...
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Full title
Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces
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TN_cdi_doaj_primary_oai_doaj_org_article_e976c5dc8d274ddfa4b6e39fe135aca9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e976c5dc8d274ddfa4b6e39fe135aca9
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ISSN
2632-2153
E-ISSN
2632-2153
DOI
10.1088/2632-2153/ad5f11
