Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures-Reference-Cited by-同舟云学术

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

Published:2021-07-07 Issue:1 Volume:155 Page:014701
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Li Zhao¹^ORCID,Bucior Benjamin J.¹^ORCID,Chen Haoyuan¹^ORCID,Haranczyk Maciej²^ORCID,Siepmann J. Ilja³^ORCID,Snurr Randall Q.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, USA

2. IMDEA Materials Institute, C/Eric Kandel 2, Getafe 28906, Madrid, Spain

3. Department of Chemistry and Chemical Theory Center, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455, USA

Funder

U.S. Department of Energy

National Energy Research Scientific Computing Center

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

https://aip.scitation.org/doi/am-pdf/10.1063/5.0050823

Reference48 articles.

1. Regression Shrinkage and Selection Via the Lasso

2. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

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