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Quantifying disorder one atom at a time using an interpretable graph neural network paradigm
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric for local disorder, called SODAS. This metric enco...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328988/ https://www.ncbi.nlm.nih.gov/pubmed/37419927 http://dx.doi.org/10.1038/s41467-023-39755-0 |