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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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| Vydáno v: | Chem Sci |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Royal Society of Chemistry
2019
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| Témata: | |
| On-line přístup: | 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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