Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table
Abstract Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Sp...
| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Article |
| Langue: | English |
| Publié: |
Nature Portfolio
2023-02-01
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| Collection: | npj Computational Materials |
| Accès en ligne: | https://doi.org/10.1038/s41524-023-00974-0 |