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Rate coefficients of the H + H2O2 → H2 + HO2 reaction on an accurate fundamental invariant-neural network potential energy surface.

Xiaoxiao LuQingyong MengXingan WangBina FuDong H Zhang
Published in: The Journal of chemical physics (2018)
The rate coefficients of the H + H2O2 → H2 + HO2 reaction are calculated using the ring polymer molecular dynamics (RPMD), quasi-classical trajectory (QCT), and canonical variational transition state theory (CVT) with small curvature tunneling (SCT) correction, in conjunction with the recently constructed fundamental invariant-neural network (FI-NN) potential energy surface (PES) [X. Lu et al., Phys. Chem. Chem. Phys. 20, 23095 (2018)]. In RPMD calculations, 32, 16, and 8 beads are used for computing the rate coefficients at 200 K ≤ T ≤ 400 K, 500 K ≤ T ≤ 700 K, and 700 K < T ≤ 1000 K, respectively. Given that the previous experimental rate coefficients vary widely, in particular, at low temperatures, the present RPMD rate coefficients agree well with most of the experimental results. In addition, comparing with some experimental values, the present QCT and CVT/SCT calculations on the FI-NN PES also predict accurate results at some temperatures. These results strongly support the accuracy of the present dynamics calculations as well as the full-dimensional FI-NN PES.
Keyphrases
  • molecular dynamics
  • neural network
  • density functional theory
  • high resolution
  • wastewater treatment
  • risk assessment
  • climate change
  • pi k akt
  • human health