Volume 212, 2018

Ab initio instanton rate theory made efficient using Gaussian process regression

Abstract

Ab initio instanton rate theory is a computational method for rigorously including tunnelling effects into the calculations of chemical reaction rates based on a potential-energy surface computed on the fly from electronic-structure theory. This approach is necessary to extend conventional transition-state theory into the deep-tunnelling regime, but it is also more computationally expensive as it requires many more ab initio calculations. We propose an approach which uses Gaussian process regression to fit the potential-energy surface locally around the dominant tunnelling pathway. The method can be converged to give the same result as from an on-the-fly ab initio instanton calculation but it requires far fewer electronic-structure calculations. This makes it a practical approach for obtaining accurate rate constants based on high-level electronic-structure methods. We show fast convergence to reproduce benchmark H + CH4 results and evaluate new low-temperature rates of H + C2H6 in full dimensionality at a UCCSD(T)-F12b/cc-pVTZ-F12 level.

Graphical abstract: Ab initio instanton rate theory made efficient using Gaussian process regression

Associated articles

Article information

Article type
Paper
Submitted
27 Apr 2018
Accepted
21 May 2018
First published
27 Jun 2018
This article is Open Access
Creative Commons BY license

Faraday Discuss., 2018,212, 237-258

Ab initio instanton rate theory made efficient using Gaussian process regression

G. Laude, D. Calderini, D. P. Tew and J. O. Richardson, Faraday Discuss., 2018, 212, 237 DOI: 10.1039/C8FD00085A

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