Deep neural network learning of complex binary sorption equilibria from molecular simulation data-Reference-Cited by-同舟云学术

Deep neural network learning of complex binary sorption equilibria from molecular simulation data

Published:2019 Issue:16 Volume:10 Page:4377-4388
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Sun Yangzesheng¹²³⁴^ORCID,DeJaco Robert F.¹²³⁴⁵^ORCID,Siepmann J. Ilja¹²³⁴⁵^ORCID

Affiliation:

1. Department of Chemistry and Chemical Theory Center

2. University of Minnesota

3. Minneapolis

4. USA

5. Department of Chemical Engineering and Materials Science

Abstract

We employed deep neural networks (NNs) as an efficient and intelligent surrogate of molecular simulations for complex sorption equilibria using probabilistic modeling.

Funder

Biomass Program

Office of Science

Basic Energy Sciences

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2019/SC/C8SC05340E

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