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Deep neural network learning of complex binary sorption equilibria from molecular simulation data
We employed deep neural networks (NNs) as an efficient and intelligent surrogate of molecular simulations for complex sorption equilibria using probabilistic modeling. Canonical (N(1)N(2)VT) Gibbs ensemble Monte Carlo simulations were performed to model a single-stage equilibrium desorptive drying p...
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| Publicado no: | Chem Sci |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Royal Society of Chemistry
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6482883/ https://ncbi.nlm.nih.gov/pubmed/31057764 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1039/c8sc05340e |
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