Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning

Predicting a priori local defects in amorphous materials remains a grand challenge. Here authors combine a rotationally non-invariant structure representation with deep-learning to predict the propensity for shear transformations of amorphous solids for different loading orientations, only given the...

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Autores principales: Zhao Fan, Evan Ma
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/fbaccc18a78f426ab79a24a83fc9e2fd
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