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Investigating the effect of textural properties on CO(2) adsorption in porous carbons via deep neural networks using various training algorithms
The adsorption of carbon dioxide (CO(2)) on porous carbon materials offers a promising avenue for cost-effective CO(2) emissions mitigation. This study investigates the impact of textural properties, particularly micropores, on CO(2) adsorption capacity. Multilayer perceptron (MLP) neural networks w...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692134/ https://www.ncbi.nlm.nih.gov/pubmed/38040890 http://dx.doi.org/10.1038/s41598-023-48683-4 |