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A neural network potential energy surface of the Li 3 system and quantum dynamics studies for the 7 Li + 6 Li 2 → 6 Li 7 Li + 6 Li reaction.

Jiapeng ZhangBayaer BurenYongqing Li
Published in: Physical chemistry chemical physics : PCCP (2024)
A high-precision global potential energy surface (PES) of the Li 3 system is constructed based on high-level ab initio calculations, and the root-mean-square error is 5.54 cm -1 . The short-range of the PES is fitted by the fundamental invariant neural network (FI-NN) method, while the long-range uses a function with an accurate asymptotic potential energy form, and the two regions are connected by a switching function. Based on the new PES, the statistical quantum-mechanical (SQM) and the time-dependent wave packet (TDWP) methods are used to study the dynamics of 7 Li + 6 Li 2 ( v = 0, j = 0) → 6 Li 7 Li + 6 Li reactions in the low collision energy region (10 -11 to 10 -3 cm -1 ) and the high collision energy region (8 to 800 cm -1 ), respectively. In the high collision energy region, the calculation results of the SQM method and the TDWP method are inconsistent, indicating that the reaction dynamics does not follow the statistical behavior in the high collision energy region. In addition, we found that the Coriolis coupling effect plays an important role in this reaction. The symmetric forward-backward scattering in the total DCS indicates that the reaction follows the complex-forming reaction mechanism.
Keyphrases
  • ion batteries
  • neural network
  • solid state
  • climate change
  • molecular dynamics simulations
  • ionic liquid