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Predicting hydrogen storage in MOFs via machine learning
The H(2) capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced from 19 databases is predicted via machine learning (ML). Using only 7 structural features as input, ML identifies 8,282 MOFs with the potential to exceed the capacities of state-of-the-art materials. The identif...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Elsevier
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276024/ https://www.ncbi.nlm.nih.gov/pubmed/34286305 http://dx.doi.org/10.1016/j.patter.2021.100291 |