Exhaustive State-to-State Cross Sections and Rate Coefficients for Inelastic N 2 -N 2 Collisions using QCT Combined with Neural Network Models.

Autor: Guo CM; Institute of Atomic and Molecular Physics, Sichuan University, Chengdu 610065, China., Zhang H; College of Physics, Sichuan University, Chengdu 610065, China., Cheng XL; Institute of Atomic and Molecular Physics, Sichuan University, Chengdu 610065, China.
Jazyk: angličtina
Zdroj: The journal of physical chemistry. A [J Phys Chem A] 2024 Jul 18; Vol. 128 (28), pp. 5435-5444. Date of Electronic Publication: 2024 Jul 02.
DOI: 10.1021/acs.jpca.4c00590
Abstrakt: Using the quasi-classical trajectory method, we systematically studied the state-to-state vibrational relaxation process of N 2 ( v 1 ) + N 2 ( v 2 ) collisions over a wide temperature range (5000-30,000 K). Different temperature dependencies of the single- and multiquantum VV and VT events in various ( v 1 , v 2 ) collisions are captured, with the dominant channel being related to the initial vibrational energy levels ( v max = 50). At a specified relative translational energy, there is a monotonic relationship of the VT cross sections with the vibrational energy level, particularly in high-energy collisions. Additionally, we constructed well-trained neural network models ( R -values reaching 0.99) using limited quasi-classical trajectory (QCT) data sets, which can be used to predict the state-to-state cross sections and rate coefficients of the VV processes N 2 ( v 1 ) + N 2 ( v 2 ) → N 2 ( v 1 - Δ v ) + N 2 ( v 2 + Δ v ) and VT processes N 2 ( v 1 ) + N 2 ( v 2 ) → N 2 ( v 1 - Δ v ) + N 2 ( v 2 ) (Δ v = ±1, ±2, ±3) for collisions with arbitrary initial vibrational states. This work not only significantly reduces computational resources but also serves as a reference for the study of the state-to-state dynamics of all four-atom collision systems in hypersonic flows.
Databáze: MEDLINE