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Machine learning determination of atomic dynamics at grain boundaries
In polycrystalline materials, grain boundaries are sites of enhanced atomic motion, but the complexity of the atomic structures within a grain boundary network makes it difficult to link the structure and atomic dynamics. Here, we use a machine learning technique to establish a connection between lo...
Tallennettuna:
| Julkaisussa: | Proc Natl Acad Sci U S A |
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| Päätekijät: | , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
National Academy of Sciences
2018
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6205477/ https://ncbi.nlm.nih.gov/pubmed/30301794 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1807176115 |
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