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具有精确长程相互作用的KRb + KRb → KRb* → K + Rb反应的全维全局势能面以及超冷条件下产物态分布的量子统计计算。

Full-Dimensional Global Potential Energy Surface for the KRb + KRb → KRb* → K + Rb Reaction with Accurate Long-Range Interactions and Quantum Statistical Calculation of the Product State Distribution under Ultracold Conditions.

作者信息

Huang Jing, Yang Dongzheng, Zuo Junxiang, Hu Xixi, Xie Daiqian, Guo Hua

机构信息

Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.

Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States.

出版信息

J Phys Chem A. 2021 Jul 22;125(28):6198-6206. doi: 10.1021/acs.jpca.1c04506. Epub 2021 Jul 12.

Abstract

A full-dimensional global potential energy surface (PES) for the KRb + KRb → KRb* → K + Rb reaction is reported based on high-level calculations. The short-range part of the PES is fit with the permutationally invariant polynomial-neural network method, while the long-range parts of the PES in both the reactant and product asymptotes are represented by an asymptotically correct form. The long- and short-range parts are connected with intermediate-range parts to make them smooth. Within a statistical quantum model, this PES reproduces both the measured loss rates of ultracold KRb molecules and the K and Rb product state distributions, underscoring the important role of tunneling in ultracold chemistry. The PES also correctly predicts the lifetime of the KRb* intermediate complex within the Rice-Ramsperger-Kassel-Marcus limit. It thus provides a reliable platform for future dynamical studies of the prototypical reaction.

摘要

基于高水平计算,报道了KRb + KRb → KRb* → K + Rb反应的全维全局势能面(PES)。PES的短程部分采用置换不变多项式神经网络方法进行拟合,而反应物和产物渐近线中PES的长程部分则由渐近正确的形式表示。长程和短程部分与中程部分相连以使其平滑。在统计量子模型中,该PES既再现了超冷KRb分子的测量损失率,也再现了K和Rb产物态分布,突出了隧穿在超冷化学中的重要作用。该PES还正确预测了KRb*中间复合物在Rice-Ramsperger-Kassel-Marcus极限内的寿命。因此,它为该典型反应的未来动力学研究提供了一个可靠的平台。

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