Full-Dimensional Neural Network Potential Energy Surface for the Photodissociation Dynamics of HNCS in the S1 band.

IF 2.7 2区 化学 Q3 CHEMISTRY, PHYSICAL
The Journal of Physical Chemistry A Pub Date : 2025-01-16 Epub Date: 2025-01-03 DOI:10.1021/acs.jpca.4c07312
Shuangrui Ma, Siting Hou, Changjian Xie
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Abstract

The full-dimensional potential energy surface (PES) for the photodissociation of HNCS in the S1(1A″) electronic state has been built up by the neural network method based on more than 48,000 ab initio points, which were calculated at the multireference configuration interaction level with Davidson correction using the augmented correlation consistent polarized valence triple-ζ basis set. It was found that two minima, namely, trans and cis isomers of HNCS, and seven stationary points exist on the S1 PES for the three dissociation pathways: HNCS(S1) → H + NCS/HNC + S(1D)/HN(1Δ) + CS(1Σ+). The dissociation energies of two lowest product channels H + NCS and HNC + S(1D) calculated on the PES are in good agreement with experimental results, validating the high accuracy of the PES. Furthermore, the quasi-classical trajectory calculations were carried out to investigate the photodissociation dynamics of HNCS(S1) at the total energy ranging from 5.0 to 6.0 eV based on the newly constructed S1 PES. It was found that two products H + NCS/HNC + S(1D) are dynamically comparable with the branching ratios of ∼1:1 at high energies, and the product HNC + S(1D) is favored at low energies, resulting from different topographies of the PES along the two dissociation pathways. Specifically, the translational energy distributions of the products H + NCS and HNC + S(1D) were found to be exceedingly different. The former behaves like a Gauss-type function with a broad width and a center of the peak at relatively high energy, while the latter is dominated by the low energies and decays heavily as the translational energy increases, shedding light on the photodissociation dynamics of HNCS in the S1 band.

S1波段HNCS光解动力学的全维神经网络势能面。
采用基于48000多个从头算点的神经网络方法,建立了HNCS在S1(1A″)电子态下光解的全维势能面(PES),并采用增广相关一致极化价三重-ζ基集在多参考构型相互作用水平上进行了Davidson校正。结果表明,HNCS(S1)→H + NCS/HNC + S(1D)/HN(1Δ) + CS(1Σ+)三种解离途径在S1 PES上存在两个最小值,即HNCS的反式和顺式异构体,以及7个平稳点。PES计算的H + NCS和HNC + S两个最低产物通道的解离能(1D)与实验结果吻合较好,验证了PES的准确性。在此基础上,利用拟经典轨迹计算研究了总能量在5.0 ~ 6.0 eV范围内HNCS(S1)的光解动力学。结果表明,两种产物H + NCS/HNC + S(1D)在高能量下具有动态可比性,分支比约为1:1,而在低能下,产物HNC + S(1D)更受青睐,这是由于PES在两种解离途径上的不同地形所致。具体来说,产物H + NCS和HNC + S(1D)的平动能分布存在很大差异。前者表现为高斯型函数,具有较宽的宽度和较高能量的峰中心,而后者则以低能为主,随着平动能的增加而严重衰减,揭示了HNCS在S1波段的光解动力学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
The Journal of Physical Chemistry A
The Journal of Physical Chemistry A 化学-物理:原子、分子和化学物理
CiteScore
5.20
自引率
10.30%
发文量
922
审稿时长
1.3 months
期刊介绍: The Journal of Physical Chemistry A is devoted to reporting new and original experimental and theoretical basic research of interest to physical chemists, biophysical chemists, and chemical physicists.
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