Machine learning of atomic dynamics and statistical surface identities in gold nanoparticles

It is known that metal nanoparticles (NPs) may be dynamic and atoms may move within them even at fairly low temperatures. Characterizing such complex dynamics is key for understanding NPs’ properties in realistic regimes, but detailed information on, e.g., the stability, survival, and interconversio...

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Detalles Bibliográficos
Autores principales: Rapetti, Daniele, Delle Piane, Massimo, Cioni, Matteo, Polino, Daniela, Ferrando, Riccardo, Pavan, Giovanni M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322832/
https://www.ncbi.nlm.nih.gov/pubmed/37407706
http://dx.doi.org/10.1038/s42004-023-00936-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322832/
https://www.ncbi.nlm.nih.gov/pubmed/37407706
http://dx.doi.org/10.1038/s42004-023-00936-z

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