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Gaussian Process Regression for Minimum Energy Path Optimization and Transition State Search
- Source :
- The Journal of Physical Chemistry - Part A; November 2019, Vol. 123 Issue: 44 p9600-9611, 12p
- Publication Year :
- 2019
-
Abstract
- We implemented a gradient-based algorithm for finding minimum energy paths (MEPs) using Gaussian process regression (GPR). A subsequent search for transition states can be performed very fast. We describe the algorithm in detail and compare its performance to the nudged elastic band (NEB) method in 27 test systems. Additionally, three different possibilities for an initial guess of the path are evaluated. We found the new optimizer to considerably decrease the number of required energy and gradient evaluations.
Details
- Language :
- English
- ISSN :
- 10895639 and 15205215
- Volume :
- 123
- Issue :
- 44
- Database :
- Supplemental Index
- Journal :
- The Journal of Physical Chemistry - Part A
- Publication Type :
- Periodical
- Accession number :
- ejs51243244
- Full Text :
- https://doi.org/10.1021/acs.jpca.9b08239