tmQM Dataset—Quantum Geometries and Properties of 86k Transition Metal Complexes-Reference-Cited by-同舟云学术

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tmQM Dataset—Quantum Geometries and Properties of 86k Transition Metal Complexes

Published:2020-11-09 Issue:12 Volume:60 Page:6135-6146
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Balcells David¹^ORCID,Skjelstad Bastian Bjerkem²^ORCID

Affiliation:

1. Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Oslo, P.O. Box 1033, Blindern, 0315 Oslo, Norway

2. Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo 001-0021, Japan

Funder

Norges Forskningsr?d

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acs.jcim.0c01041

Reference92 articles.

1. How to explore chemical space using algorithms and automation

2. Machine learning for molecular and materials science

3. Machine learning unifies the modeling of materials and molecules

4. Machine learning for chemical discovery

5. The Chemical Space Project

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