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Inverse design with deep generative models: next step in materials discovery
Data-driven inverse design for inorganic functional materials is a rapidly emerging field, which aims to automatically design innovative materials with target properties and to enable property-to-structure material discovery.
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385454/ https://www.ncbi.nlm.nih.gov/pubmed/35992238 http://dx.doi.org/10.1093/nsr/nwac111 |