2 papers
cond-mat.dis-nn2024
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang +2
Metallic Glasses (MGs) are widely used materials that are stronger than steel while being shapeable as plastic. While understanding the structure-property relationship of MGs remai…
cond-mat.mtrl-sci2024
Inverse designing metamaterials with programmable nonlinear functional responses in graph space
Marco Maurizi, Derek Xu, Yu-Tong Wang +9
Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, an…