Quantum-classical rate coefficient datasets of vibrational energy transfer in carbon monoxide based on highly accurate potential energy surface
文献类型:期刊论文
作者 | Hong QZ(洪启臻)4![]() ![]() ![]() |
刊名 | JOURNAL OF CHEMICAL PHYSICS
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出版日期 | 2024-02-28 |
卷号 | 160期号:8页码:15 |
ISSN号 | 0021-9606 |
DOI | 10.1063/5.0189772 |
通讯作者 | Sun, Quanhua(qsun@imech.ac.cn) ; Li, Jun(jli15@cqu.edu.cn) |
英文摘要 | A merged potential energy surface (PES) is introduced for CO + CO collisions by combining a recent full-dimensional ab initio PES [Chen et al. J. Chem. Phys. 153, 054310 (2020)] and analytical long-range multipolar interactions. This merged PES offers a double advantage: it retains the precision of the ab initio PES in describing the van der Waals well and repulsive short range while providing an accurate physical description of long-range interaction; it significantly reduces the computational time required for trajectory integration since the long-range portion of the ab initio PES (involving numerous neural network fitting parameters) is now replaced by the analytical model potential. Based on the present merged PES, mixed Quantum-Classical (MQC) calculations, which capture quantum effects related to vibrational motion, align with a range of experimental data, including transport properties, vibrational energy transfer between CO and its isotoplogues, as well as rate coefficients for V-V and V-T/R processes. Notably, the original ab initio PES yields V-T/R rate coefficients at low temperatures that are significantly higher than the experimental data due to the artificial contribution of its unphysical long-range potential. In addition to conducting extensive MQC calculations to obtain raw data for V-V and V-T/R rate coefficients, we employ Gaussian process regression to predict processes lacking computed MQC data, thereby completing the considered V-V and V-T/R datasets. These extensive rate coefficient datasets, particularly for V-T/R processes, are unprecedented and reveal the significant role played by V-T/R processes at high temperatures, emphasizing the necessity of incorporating both V-V and V-T/R processes in the applications. |
分类号 | 二类/Q1 |
WOS关键词 | RATE CONSTANTS ; CO-CO ; TRANSFER PROBABILITIES ; POLYATOMIC GASES ; CROSS-SECTIONS ; RELAXATION ; DIMER ; CONDUCTIVITY ; COLLISIONS ; STATES |
资助项目 | State Key Laboratory of High Temperature Gas Dynamics, Chinese Academy of Scienceshttps://doi.org/10.13039/501100015363[2021KF04] ; State Key Laboratory of High-Temperature Gas Dynamics Open Fund[2022M723233] ; China Postdoctoral Science Foundation[12302391] ; National Natural Science Foundation of China |
WOS研究方向 | Chemistry ; Physics |
语种 | 英语 |
WOS记录号 | WOS:001178229000003 |
资助机构 | State Key Laboratory of High Temperature Gas Dynamics, Chinese Academy of Scienceshttps://doi.org/10.13039/501100015363 ; State Key Laboratory of High-Temperature Gas Dynamics Open Fund ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China |
其他责任者 | Sun, Quanhua ; Li, Jun |
源URL | [http://dspace.imech.ac.cn/handle/311007/94872] ![]() |
专题 | 力学研究所_高温气体动力学国家重点实验室 |
作者单位 | 1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 2.Chongqing Univ, Sch Chem & Chem Engn, Chongqing Key Lab Theoret & Computat Chem, Chongqing 401331, Peoples R China; 3.Univ G Annunzio Chieti Pescara, Dipartimento Farm, Via Vestini, I-66100 Chieti, Italy; 4.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing 100190, Peoples R China; |
推荐引用方式 GB/T 7714 | Hong QZ,Storchi, Loriano,Coletti, Cecilia,et al. Quantum-classical rate coefficient datasets of vibrational energy transfer in carbon monoxide based on highly accurate potential energy surface[J]. JOURNAL OF CHEMICAL PHYSICS,2024,160(8):15. |
APA | 洪启臻,Storchi, Loriano,Coletti, Cecilia,Li, Jia,孙泉华,&Li, Jun.(2024).Quantum-classical rate coefficient datasets of vibrational energy transfer in carbon monoxide based on highly accurate potential energy surface.JOURNAL OF CHEMICAL PHYSICS,160(8),15. |
MLA | 洪启臻,et al."Quantum-classical rate coefficient datasets of vibrational energy transfer in carbon monoxide based on highly accurate potential energy surface".JOURNAL OF CHEMICAL PHYSICS 160.8(2024):15. |
入库方式: OAI收割
来源:力学研究所
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