Evaluation of Machine Learning Interatomic Potentials for Gold Nanoparticles—Transferability towards Bulk

We analyse the efficacy of machine learning (ML) interatomic potentials (IP) in modelling gold (Au) nanoparticles. We have explored the transferability of these ML models to larger systems and established simulation times and size thresholds necessary for accurate interatomic potentials. To achieve...

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Detalles Bibliográficos
Autores principales: Fronzi, Marco, Amos, Roger D., Kobayashi, Rika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303715/
https://www.ncbi.nlm.nih.gov/pubmed/37368262
http://dx.doi.org/10.3390/nano13121832

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303715/
https://www.ncbi.nlm.nih.gov/pubmed/37368262
http://dx.doi.org/10.3390/nano13121832

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