Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning-Reference-Cited by-同舟云学术

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Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning

Published:2021-09-24 Issue:10 Volume:17 Page:6193-6202
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Roet Sander¹^ORCID,Daub Christopher D.²^ORCID,Riccardi Enrico³^ORCID

Affiliation:

1. Department of Chemistry, Norwegian University of Science and Technology, Høgskoleringen 5, 7491 Trondheim, Norway

2. Department of Chemistry, University of Helsinki, P.O. Box 55, FI-00014 Helsinki, Finland

3. Department of Informatics, UiO, Gaustadalléen 23B, 0373 Oslo, Norway

Funder

Academy of Finland

Jane ja Aatos Erkon S????ti??

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.1c00458

Reference59 articles.

1. A large and ubiquitous source of atmospheric formic acid

2. A Large Underestimate of Formic Acid from Tropical Fires: Constraints from Space-Borne Measurements

3. An Ab Initio Molecular Dynamics Study of the Hydrolysis Reaction of Sulfur Trioxide Catalyzed by a Formic Acid or Water Molecule

4. Path sampling for atmospheric reactions: formic acid catalysed conversion of SO3 + H2O to H2SO4

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