Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks
<jats:title>Abstract</jats:title><jats:p>Structural defects are abundant in solids, and vital to the macroscopic materials properties. However, a defect-property linkage typically requires significant efforts from experiments or simulations, and often contains limited information d...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2023
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| Online Access: | https://hdl.handle.net/1721.1/148573 |