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Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt
Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440250/ https://www.ncbi.nlm.nih.gov/pubmed/36055982 http://dx.doi.org/10.1038/s41467-022-32294-0 |