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Predicting ionic conductivity in solids from the machine-learned potential energy landscape

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Maevskiy, Artem, Carvalho, Alexandra, Sataev, Emil, Turchyna, Volha, Noori, Keian, Rodin, Aleksandr, Neto, A. H. Castro, Ustyuzhanin, Andrey
Format:	Preprint
Publié:	2024
Sujets:	Materials Science Machine Learning
Accès en ligne:	Acceder al recurso
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