Skip to main content

Theoretical studies on triplet-state driven dissociation of formaldehyde by quasi-classical molecular dynamics simulation on machine-learning potential energy surface.

Publication ,  Journal Article
Lin, S; Peng, D; Yang, W; Gu, FL; Lan, Z
Published in: The Journal of chemical physics
December 2021

The H-atom dissociation of formaldehyde on the lowest triplet state (T1) is studied by quasi-classical molecular dynamic simulations on the high-dimensional machine-learning potential energy surface (PES) model. An atomic-energy based deep-learning neural network (NN) is used to represent the PES function, and the weighted atom-centered symmetry functions are employed as inputs of the NN model to satisfy the translational, rotational, and permutational symmetries, and to capture the geometry features of each atom and its individual chemical environment. Several standard technical tricks are used in the construction of NN-PES, which includes the application of clustering algorithm in the formation of the training dataset, the examination of the reliability of the NN-PES model by different fitted NN models, and the detection of the out-of-confidence region by the confidence interval of the training dataset. The accuracy of the full-dimensional NN-PES model is examined by two benchmark calculations with respect to ab initio data. Both the NN and electronic-structure calculations give a similar H-atom dissociation reaction pathway on the T1 state in the intrinsic reaction coordinate analysis. The small-scaled trial dynamics simulations based on NN-PES and ab initio PES give highly consistent results. After confirming the accuracy of the NN-PES, a large number of trajectories are calculated in the quasi-classical dynamics, which allows us to get a better understanding of the T1-driven H-atom dissociation dynamics efficiently. Particularly, the dynamics simulations from different initial conditions can be easily simulated with a rather low computational cost. The influence of the mode-specific vibrational excitations on the H-atom dissociation dynamics driven by the T1 state is explored. The results show that the vibrational excitations on symmetric C-H stretching, asymmetric C-H stretching, and C=O stretching motions always enhance the H-atom dissociation probability obviously.

Duke Scholars

Published In

The Journal of chemical physics

DOI

EISSN

1089-7690

ISSN

0021-9606

Publication Date

December 2021

Volume

155

Issue

21

Start / End Page

214105

Related Subject Headings

  • Chemical Physics
  • 51 Physical sciences
  • 40 Engineering
  • 34 Chemical sciences
  • 09 Engineering
  • 03 Chemical Sciences
  • 02 Physical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Lin, S., Peng, D., Yang, W., Gu, F. L., & Lan, Z. (2021). Theoretical studies on triplet-state driven dissociation of formaldehyde by quasi-classical molecular dynamics simulation on machine-learning potential energy surface. The Journal of Chemical Physics, 155(21), 214105. https://doi.org/10.1063/5.0067176
Lin, Shichen, Daoling Peng, Weitao Yang, Feng Long Gu, and Zhenggang Lan. “Theoretical studies on triplet-state driven dissociation of formaldehyde by quasi-classical molecular dynamics simulation on machine-learning potential energy surface.The Journal of Chemical Physics 155, no. 21 (December 2021): 214105. https://doi.org/10.1063/5.0067176.
Lin, Shichen, et al. “Theoretical studies on triplet-state driven dissociation of formaldehyde by quasi-classical molecular dynamics simulation on machine-learning potential energy surface.The Journal of Chemical Physics, vol. 155, no. 21, Dec. 2021, p. 214105. Epmc, doi:10.1063/5.0067176.

Published In

The Journal of chemical physics

DOI

EISSN

1089-7690

ISSN

0021-9606

Publication Date

December 2021

Volume

155

Issue

21

Start / End Page

214105

Related Subject Headings

  • Chemical Physics
  • 51 Physical sciences
  • 40 Engineering
  • 34 Chemical sciences
  • 09 Engineering
  • 03 Chemical Sciences
  • 02 Physical Sciences