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A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses
When metallic glasses (MGs) are subjected to mechanical loads, the plastic response of atoms is non-uniform. However, the extent and manner in which atomic environment signatures present in the undeformed structure determine this plastic heterogeneity remain elusive. Here, we demonstrate that novel...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895099/ https://www.ncbi.nlm.nih.gov/pubmed/31804485 http://dx.doi.org/10.1038/s41467-019-13511-9 |