Generating transition states of isomerization reactions with deep learning-Reference-Cited by-同舟云学术

Generating transition states of isomerization reactions with deep learning

Published:2020 Issue:41 Volume:22 Page:23618-23626
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Pattanaik Lagnajit¹²³⁴^ORCID,Ingraham John B.⁵²³⁴,Grambow Colin A.¹²³⁴^ORCID,Green William H.¹²³⁴^ORCID

Affiliation:

1. Department of Chemical Engineering

2. Massachusetts Institute of Technology

3. Cambridge

4. USA

5. Computer Science and Artificial Intelligence Laboratory

Abstract

We develop a deep learning architecture to predict 3D transition state geometries. The new method generates structures more rapidly than existing QM methods.

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2020/CP/D0CP04670A

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