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An Ecosystem for Digital Reticular Chemistry
[Image: see text] The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of...
Autores principales: | Jablonka, Kevin Maik, Rosen, Andrew S., Krishnapriyan, Aditi S., Smit, Berend |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10141625/ https://www.ncbi.nlm.nih.gov/pubmed/37122448 http://dx.doi.org/10.1021/acscentsci.2c01177 |
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