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Ring-polymer molecular dynamics study on rate coefficient of the barrierless OH + CO system at low temperature.

Qingyong MengJun Chen
Published in: The Journal of chemical physics (2019)
Based on the recently constructed neural-network potential energy surface [Chen et al., J. Chem. Phys. 138, 221104 (2013)], ring-polymer molecular dynamics (RPMD) calculations are performed to compute rate coefficients of the barrierless OH + CO system at T ≤ 500 K. To recover the barrierless feature, a Lindemann-Hinshelwood-type mechanism and hence a reduced rate coefficient are used to approximate the overall rate coefficient. An agreement between RPMD and experimental rate coefficients can be found. These RPMD results reproduce correctly the temperature-independence of the overall rate coefficient. Finally, potential sources of errors in the present RPMD calculations are discussed.
Keyphrases
  • molecular dynamics
  • density functional theory
  • neural network
  • diffusion weighted imaging
  • magnetic resonance imaging
  • molecular dynamics simulations
  • deep learning
  • quality improvement
  • climate change
  • human health