Journal of Computational Chemistry, volume 43, issue 21, pages 1434-1441
Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules
Publication type: Journal Article
Publication date: 2022-06-09
Journal:
Journal of Computational Chemistry
Quartile SCImago
Q1
Quartile WOS
Q3
Impact factor: 3
ISSN: 01928651, 1096987X
General Chemistry
Computational Mathematics
Abstract
Finding global and local minima on the potential energy surface is a key task for most studies in computational chemistry. Having a set of possible conformations for chemical structures and their corresponding energies, one can judge their chemical activity, understand the mechanisms of reactions, describe the formation of metal‐ligand and ligand‐protein complexes, and so forth. Despite the fact that the interest in various minima search algorithms in computational chemistry arose a while ago (during the formation of this science), new methods are still emerging. These methods allow to perform conformational analysis and geometry optimization faster, more accurately, or for more specific tasks. This article presents the application of a novel global geometry optimization approach based on the Tree Parzen Estimator method. For benchmarking, a database of small organic molecule geometries in the global minimum conformation was created, as well as a software package to perform the tests.
Citations by journals
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Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
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Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
1 publication, 50%
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Journal of Failure Analysis and Prevention
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Journal of Failure Analysis and Prevention
1 publication, 50%
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1
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Citations by publishers
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2
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Springer Nature
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Springer Nature
2 publications, 100%
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2
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Andreadi N. et al. Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules // Journal of Computational Chemistry. 2022. Vol. 43. No. 21. pp. 1434-1441.
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Andreadi N., Zankov D., Karpov K., Mitrofanov A. Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules // Journal of Computational Chemistry. 2022. Vol. 43. No. 21. pp. 1434-1441.
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TY - JOUR
DO - 10.1002/jcc.26947
UR - https://doi.org/10.1002%2Fjcc.26947
TI - Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules
T2 - Journal of Computational Chemistry
AU - Zankov, Dmitry
AU - Karpov, Kirill
AU - Andreadi, Nikolai
AU - Mitrofanov, Artem
PY - 2022
DA - 2022/06/09 00:00:00
PB - Wiley
SP - 1434-1441
IS - 21
VL - 43
SN - 0192-8651
SN - 1096-987X
ER -
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@article{2022_Andreadi,
author = {Dmitry Zankov and Kirill Karpov and Nikolai Andreadi and Artem Mitrofanov},
title = {Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules},
journal = {Journal of Computational Chemistry},
year = {2022},
volume = {43},
publisher = {Wiley},
month = {jun},
url = {https://doi.org/10.1002%2Fjcc.26947},
number = {21},
pages = {1434--1441},
doi = {10.1002/jcc.26947}
}
Cite this
MLA
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Andreadi, Nikolai, et al. “Tree Parzen estimator for global geometry optimization: A benchmark and database of experimental gas-phase structures of organic molecules.” Journal of Computational Chemistry, vol. 43, no. 21, Jun. 2022, pp. 1434-1441. https://doi.org/10.1002%2Fjcc.26947.