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An invertible, invariant crystal representation for inverse design of solid-state materials using generative deep learning
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. However, the...
| 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/PMC10622439/ https://www.ncbi.nlm.nih.gov/pubmed/37919277 http://dx.doi.org/10.1038/s41467-023-42870-7 |