Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics
Abstract A data-driven framework is presented for building magneto-elastic machine-learning interatomic potentials (ML-IAPs) for large-scale spin-lattice dynamics simulations. The magneto-elastic ML-IAPs are constructed by coupling a collective atomic spin model with an ML-IAP. Together they represe...
Enregistré dans:
| Auteurs principaux: | , , , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/d348af2bd3da41768c9cb3ef7706b759 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Soyez le premier à ajouter un commentaire!