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Iterative training set refinement enables reactive molecular dynamics via machine learned forces
Machine learning approaches have been successfully employed in many fields of computational chemistry and physics. However, atomistic simulations driven by machine-learned forces are still very challenging. Here we show that reactive self-sputtering from a beryllium surface can be simulated using ne...
Autores principales: | Chen, Lei, Sukuba, Ivan, Probst, Michael, Kaiser, Alexander |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9049032/ https://www.ncbi.nlm.nih.gov/pubmed/35495270 http://dx.doi.org/10.1039/c9ra09935b |
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