Machine Learning Analysis of Direct Dynamics Trajectory Outcomes for Thermal Deazetization of 2,3-Diazabicyclo[2.2.1]hept-2-ene-Reference-Cited by-同舟云学术

Machine Learning Analysis of Direct Dynamics Trajectory Outcomes for Thermal Deazetization of 2,3-Diazabicyclo[2.2.1]hept-2-ene

Published:2020-05-15 Issue:23 Volume:124 Page:4813-4826
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Rollins Nick¹,Pugh Samuel L.¹,Maley Steven M.¹^ORCID,Grant Benjamin O.¹,Hamilton R. Spencer¹,Teynor Matthew S.¹^ORCID,Carlsen Ryan¹,Jenkins Jordan R.¹,Ess Daniel H.¹^ORCID

Affiliation:

1. Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States

Funder

Brigham Young University

Basic Energy Sciences

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.9b10410

Reference48 articles.

1. Post-transition state bifurcations gain momentum – current state of the field

2. “Concerted” Transition State, Stepwise Mechanism. Dynamics Effects in C2-C6 Enyne Allene Cyclizations

3. Dynamics and the Failure of Transition State Theory in Alkene Hydroboration

4. Dynamics of the biradical mediating vinylcyclopropane–cyclopentene rearrangement

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