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...
| Главные авторы: | , , , , , , , , , , |
|---|---|
| Формат: | Статья |
| Язык: | English |
| Опубликовано: |
Nature Portfolio
2023-02-01
|
| Серии: | npj Computational Materials |
| Online-ссылка: | https://doi.org/10.1038/s41524-023-00974-0 |