An invertible, invariant crystal representation for inverse design of solid-state materials using generative deep learning
Abstract The past decade has witnessed rapid progress in deep learning for molecular design, owing to the availability of invertible and invariant representations for molecules such as simplified molecular-input line-entry system (SMILES), which has powered cheminformatics since the late 1980s. Howe...
| Những tác giả chính: | , , , , , , |
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| Định dạng: | Bài viết |
| Ngôn ngữ: | English |
| Được phát hành: |
Nature Portfolio
2023-11-01
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| Loạt: | Nature Communications |
| Truy cập trực tuyến: | https://doi.org/10.1038/s41467-023-42870-7 |