Big-Data Science in Porous Materials: Materials Genomics and Machine Learning-Reference-Cited by-同舟云学术

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

Published:2020-06-10 Issue:16 Volume:120 Page:8066-8129
ISSN:0009-2665
Container-title:Chemical Reviews
language:en
Short-container-title:Chem. Rev.

Author:

Jablonka Kevin Maik¹^ORCID,Ongari Daniele¹^ORCID,Moosavi Seyed Mohamad¹^ORCID,Smit Berend¹^ORCID

Affiliation:

1. Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques (ISIC), École Polytechnique Fédérale de Lausanne (EPFL), Sion, Switzerland

Funder

Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Subject

General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.0c00004

Reference576 articles.

1. The Chemistry and Applications of Metal-Organic Frameworks

2. Computation-Ready, Experimental Metal–Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals

3. Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019

4. Development of a Cambridge Structural Database Subset: A Collection of Metal–Organic Frameworks for Past, Present, and Future

5. Computational development of the nanoporous materials genome

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