Constructing machine learning potential for metal nanoparticles of varying sizes via basin-hoping Monte Carlo and active learning
Nanoparticles, distinguished by their unique chemical and physical properties, have emerged as focal points within the realm of materials science. Traditional theoretical approaches for atomic simulations mainly include empirical force field and ab initio simulations, with the former offering effici...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science Press
2024-03-01
|
| Series: | National Science Open |
| Subjects: | |
| Online Access: | https://www.sciengine.com/doi/10.1360/nso/20230088 |