Invariant manifolds and rate constants in driven chemical reactions
Matthias Feldmaier
Philippe Schraft
Robin Bardakcioglu
Johannes Reiff
Melissa Lober
Martin Tschope
Andrej Junginger
Jorg Main
Thomas Bartsch
Rigoberto Hernandez
2134/37223
https://repository.lboro.ac.uk/articles/journal_contribution/Invariant_manifolds_and_rate_constants_in_driven_chemical_reactions/9377441
Reaction rates of chemical reactions under nonequilibrium conditions can be determined through the construction of the normally hyperbolic invariant manifold (NHIM) [and moving dividing surface (DS)] associated with the transition state trajectory. Here, we extend our recent methods by constructing points on the NHIM accurately even for multidimensional cases. We also advance the implementation of machine learning approaches to construct smooth versions of the NHIM from a known high-accuracy set of its points. That is, we expand on our earlier use of neural nets and introduce the use of Gaussian process regression for the determination of the NHIM. Finally, we compare and contrast all of these methods for a challenging two-dimensional model barrier case so as to illustrate their accuracy and general applicability.
2019-03-18 13:38:25
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Mathematical Sciences not elsewhere classified