A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses
oleh: Qi Wang, Anubhav Jain
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2019-12-01 |
Deskripsi
Understanding plastic deformation in metallic glasses is challenging due to their heterogeneous atomic environments. Here the authors propose a machine learning approach generalizable across compositions to predict the structural features from which plastic deformation is initiated in a metallic glass.