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钠原子(单重态)与氢原子反应生成氢化钠和氢原子的从头算神经网络势能面及量子动力学计算

Ab Initio Neural Network Potential Energy Surface and Quantum Dynamics Calculations on Na(S) + H → NaH + H Reaction.

作者信息

Liu Siwen, Cheng Huiying, Cao Furong, Sun Jingchang, Yang Zijiang

机构信息

School of Physics and Electronic Technology, Liaoning Normal University, Dalian 116029, China.

出版信息

Molecules. 2024 Oct 14;29(20):4871. doi: 10.3390/molecules29204871.

DOI:10.3390/molecules29204871
PMID:39459240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11510301/
Abstract

The collisions between Na atoms and H molecules are of great significance in the field of chemical reaction dynamics, but the corresponding dynamics results of ground-state reactions have not been reported experimentally or theoretically. Herein, a global and high-precision potential energy surface (PES) of NaH (1') is constructed by the neural network model based on 21,873 high-level ab initio points. On the newly constructed PES, the quantum dynamics calculations on the Na(S) + H( = 0, = 0) → NaH + H reaction are carried out using the time-dependent wave packet method to study the microscopic reaction mechanism at the state-to-state level. The calculated results show that the low-vibrational products are mainly formed by the dissociation of the triatomic complex; whereas, the direct reaction process dominates the generation of the products with high-vibrational states. The reaction generally follows the direct H-abstraction process, and there is also the short-lived complex-forming mechanism that occurs when the collision energy exceeds the reaction threshold slightly. The PES could be used to further study the stereodynamics effects of isotope substitution and rovibrational excitations on the title reaction, and the presented dynamics data would provide an important reference on the corresponding experimental research at a higher level.

摘要

钠原子与氢分子之间的碰撞在化学反应动力学领域具有重要意义,但基态反应的相应动力学结果尚未有实验或理论报道。在此,基于21873个高水平从头算点,通过神经网络模型构建了NaH(1')的全局高精度势能面(PES)。在新构建的PES上,采用含时波包方法对Na(S)+H( = 0, = 0)→NaH + H反应进行量子动力学计算,以研究态-态水平的微观反应机理。计算结果表明,低振动产物主要由三原子复合物的解离形成;而高振动态产物的生成则以直接反应过程为主导。该反应一般遵循直接氢提取过程,当碰撞能量略超过反应阈值时,还会出现短暂的复合物形成机制。该PES可用于进一步研究同位素取代和振转激发对标题反应的立体动力学效应,所呈现的动力学数据将为更高水平的相应实验研究提供重要参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/52d82c7a46ac/molecules-29-04871-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/c173e7e8c1aa/molecules-29-04871-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/34fde49ce4e0/molecules-29-04871-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/a3f7ee60a4a0/molecules-29-04871-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/20684f3614d3/molecules-29-04871-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/c4f435510638/molecules-29-04871-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/2d7b963b42ee/molecules-29-04871-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/a54ca335b156/molecules-29-04871-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/e80dfcd3548e/molecules-29-04871-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/6de2f10c4300/molecules-29-04871-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/52d82c7a46ac/molecules-29-04871-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/c173e7e8c1aa/molecules-29-04871-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/34fde49ce4e0/molecules-29-04871-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/a3f7ee60a4a0/molecules-29-04871-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/20684f3614d3/molecules-29-04871-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/c4f435510638/molecules-29-04871-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/2d7b963b42ee/molecules-29-04871-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/a54ca335b156/molecules-29-04871-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/e80dfcd3548e/molecules-29-04871-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/6de2f10c4300/molecules-29-04871-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a9b/11510301/52d82c7a46ac/molecules-29-04871-g010.jpg

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2
Machine Learning of Reactive Potentials.反应电位的机器学习
Annu Rev Phys Chem. 2024 Jun;75(1):371-395. doi: 10.1146/annurev-physchem-062123-024417.
3
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J Phys Chem A. 2024 Jul 4;128(26):5115-5127. doi: 10.1021/acs.jpca.4c01891. Epub 2024 Jun 18.
4
Accurate fundamental invariant-neural network representation of potential energy surfaces.势能面的精确基本不变神经网络表示。
Natl Sci Rev. 2023 Dec 20;10(12):nwad321. doi: 10.1093/nsr/nwad321. eCollection 2023 Dec.
5
Comparison of multifidelity machine learning models for potential energy surfaces.用于势能面的多保真度机器学习模型比较
J Chem Phys. 2023 Jul 28;159(4). doi: 10.1063/5.0158919.
6
Global and Full-Dimensional Potential Energy Surfaces of the N + O Reaction for Hyperthermal Collisions.N + O 反应的超热碰撞的全局和全维势能面。
J Phys Chem A. 2023 May 11;127(18):4027-4042. doi: 10.1021/acs.jpca.3c01065. Epub 2023 May 2.
7
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J Phys Chem A. 2022 Apr 28;126(16):2453-2462. doi: 10.1021/acs.jpca.2c00114. Epub 2022 Apr 18.
8
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Phys Chem Chem Phys. 2022 May 4;24(17):10160-10167. doi: 10.1039/d2cp00870j.
9
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J Phys Chem A. 2021 Nov 25;125(46):10111-10120. doi: 10.1021/acs.jpca.1c08105. Epub 2021 Nov 12.
10
Collision-induced and complex-mediated roaming dynamics in the H + CH → H + CH reaction.H + CH → H + CH反应中碰撞诱导及复杂介导的漫游动力学
Chem Sci. 2020 Jan 10;11(8):2148-2154. doi: 10.1039/c9sc05951b.