Nature Communications (Mar 2021)
Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning
Abstract
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.