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

Autor: Zhao Fan, Evan Ma
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-021-21806-z
Popis: 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 static structure.
Databáze: Directory of Open Access Journals