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Quasi-Classical Trajectory Dynamics Study of the Cl(2P) + C2H6 → HCl(v,j) + C2H5 Reaction. Comparison with Experiment.

Joaquin Espinosa-GarciaEmilio Martínez-NúñezCipriano Rangel
Published in: The journal of physical chemistry. A (2018)
To understand and simulate the dynamics behavior of the title reaction, QCT calculations were performed on a recently developed global analytical potential energy surface, PES-2017. These calculations combine the classical description of the dynamics with pseudoquantization in the reactants and products to perform a theoretical/experimental comparison on the same footing. Thus, in the products a series of constraints are included to analyze the HCl(v = 0,j) product, which is experimentally detected. At collision energies of 5.5 and 6.7 kcal mol-1 the largest fraction of available energy is deposited as translation, 67%, while the ethyl radical shows significant internal energy, 27%, and so it does not act as a spectator of the reaction, thus reproducing recent experimental evidence. The HCl(v=0, j) rotational distribution is cold, peaking at j = 2, only one unit hotter than experiment, which represents an error of 0.12 kcal mol-1. At a collision energy of 5.5 kcal mol-1 product translational distribution is slightly hotter than experiment, but at 6.7 kcal mol-1 agreement with recent experiments is practically quantitative, suggesting that the first experiments should be revised. In addition, we observe that the HCl(v=0, j) scattering distribution shifts from isotropic at low values of j to backward at high values of j, which is in agreement with experimental data. Finally, no evidence was found for the "chattering" mechanism suggested to explain the low translational energy of the HCl product in the backward scattering region. In sum, agreement with experiments of a series of sensible dynamic properties permits us to be optimistic on the quality and accuracy of the theoretical tools used in the present work, QCT and PES-2017.
Keyphrases
  • density functional theory
  • molecular dynamics
  • molecular dynamics simulations
  • high resolution
  • monte carlo
  • machine learning
  • risk assessment
  • liquid chromatography