INDEEDopt: a deep learning-based ReaxFF parameterization framework
Abstract Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods. The optimization of the parameters is complex and requires the development of new techniques. Here, we propose an INiti...
Enregistré dans:
| Auteurs principaux: | , , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/e38e18c02dd2449aa860d83c0501a7d3 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|