A Universal Machine Learning Algorithm for Large-Scale Screening of Materials-Reference-Cited by-同舟云学术

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A Universal Machine Learning Algorithm for Large-Scale Screening of Materials

Published:2020-02-04 Issue:8 Volume:142 Page:3814-3822
ISSN:0002-7863
Container-title:Journal of the American Chemical Society
language:en
Short-container-title:J. Am. Chem. Soc.

Author:

Fanourgakis George S.¹,Gkagkas Konstantinos²^ORCID,Tylianakis Emmanuel³,Froudakis George E.¹^ORCID

Affiliation:

1. Department of Chemistry, University of Crete, Voutes Campus, GR-70013 Heraklion, Crete, Greece

2. Advanced Technology Division, Toyota Motor Europe NV/SA, Technical Center, Hoge Wei 33B, 1930 Zaventem, Belgium

3. Department of Materials Science and Technology, University of Crete, Voutes Campus, GR-70013, Heraklion, Crete, Greece

Funder

Toyota Motor Europe NV/SA

Publisher

American Chemical Society (ACS)

Subject

Colloid and Surface Chemistry,Biochemistry,General Chemistry,Catalysis

Link

https://pubs.acs.org/doi/pdf/10.1021/jacs.9b11084

Reference25 articles.

1. Hydrogen Storage in Microporous Metal-Organic Frameworks

2. Effects of Functionalization, Catenation, and Variation of the Metal Oxide and Organic Linking Units on the Low-Pressure Hydrogen Adsorption Properties of Metal−Organic Frameworks

3. Characterization of H2 Binding Sites in Prototypical Metal−Organic Frameworks by Inelastic Neutron Scattering

4. Gas Adsorption Sites in a Large-Pore Metal-Organic Framework

5. Chemically intuited, large-scale screening of MOFs by machine learning techniques

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