Issue 20, 2023

Dynamics study of the post-transition-state-bifurcation process of the (HCOOH)H+ → CO + H3O+/HCO+ + H2O dissociation: application of machine-learning techniques

Abstract

The process of protonated formic acid dissociating from the transition state was studied using ring-polymer molecular dynamics (RPMD), classical MD, and quasi-classical trajectory (QCT) simulations. Temperature had a strong influence on the branching fractions for the HCO+ + H2O and CO + H3O+ dissociation channels. The RPMD and classical MD simulations showed similar behavior, but the QCT dynamics were significantly different owing to the excess energies in the quasi-classical trajectories. Machine-learning analysis identified several key features in the phase information of the vibrational motions at the transition state. We found that the initial configuration and momentum of a hydrogen atom connected to a carbon atom and the shrinking coordinate of the CO bond at the transition state play a role in the dynamics of HCO+ + H2O production.

Graphical abstract: Dynamics study of the post-transition-state-bifurcation process of the (HCOOH)H+ → CO + H3O+/HCO+ + H2O dissociation: application of machine-learning techniques

Supplementary files

Article information

Article type
Paper
Submitted
17 Jan 2023
Accepted
03 May 2023
First published
04 May 2023
This article is Open Access
Creative Commons BY license

Phys. Chem. Chem. Phys., 2023,25, 14016-14027

Dynamics study of the post-transition-state-bifurcation process of the (HCOOH)H+ → CO + H3O+/HCO+ + H2O dissociation: application of machine-learning techniques

T. Murakami, S. Ibuki, Y. Hashimoto, Y. Kikuma and T. Takayanagi, Phys. Chem. Chem. Phys., 2023, 25, 14016 DOI: 10.1039/D3CP00252G

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