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Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics
We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species an...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Royal Society of Chemistry
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5625287/ https://www.ncbi.nlm.nih.gov/pubmed/28989618 http://dx.doi.org/10.1039/c7sc01052d |