A neural network potential energy surface of the Li3 system and quantum dynamics studies for the 7Li + 6Li2 → 6Li7Li + 6Li reaction

Abstract

A high-precision global potential energy surface (PES) of the Li₃ 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 ⁷Li + ⁶Li₂ (v = 0, j = 0) → ⁶Li⁷Li + ⁶Li 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.