Machine learning of atomic dynamics and statistical surface identities in gold nanoparticles
Abstract 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 inter...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
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| Series: | Communications Chemistry |
| Online Access: | https://doi.org/10.1038/s42004-023-00936-z |