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...

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Autores principales: Mert Y. Sengul, Yao Song, Nadire Nayir, Yawei Gao, Ying Hung, Tirthankar Dasgupta, Adri C. T. van Duin
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/e38e18c02dd2449aa860d83c0501a7d3
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