Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space-Reference-Cited by-同舟云学术

Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space

Published:2021-08-14 Issue:6 Volume:155 Page:064105
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Heinen Stefan¹²^ORCID,von Rudorff Guido Falk¹²^ORCID,von Lilienfeld O. Anatole¹²^ORCID

Affiliation:

1. Faculty of Physics, University of Vienna, Kolingasse 14-16, AT-1090 Wien, Austria

2. Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials (MARVEL), Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland

Funder

H2020 European Research Council

National Center of Competence in Research Materials' Revolution: Computational Design and Discovery of Novel Materials

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0059742

Reference69 articles.

1. Steric Retardation of SN2 Reactions in the Gas Phase and Solution

2. Controlling an organic synthesis robot with machine learning to search for new reactivity

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4. autodE: Automated Calculation of Reaction Energy Profiles— Application to Organic and Organometallic Reactions

5. Methods for exploring reaction space in molecular systems

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