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氧在铝(111)表面的解离化学吸附:基于关联波函数的势能面上的动力学

Dissociative Chemisorption of O on Al(111): Dynamics on a Correlated Wave-Function-Based Potential Energy Surface.

作者信息

Yin Rongrong, Zhang Yaolong, Libisch Florian, Carter Emily A, Guo Hua, Jiang Bin

机构信息

Hefei National Laboratory for Physical Science at the Microscale, Department of Chemical Physics , University of Science and Technology of China , Hefei , Anhui 230026 , China.

Institute for Theoretical Physics , Vienna University of Technology , 1040 Vienna , Austria.

出版信息

J Phys Chem Lett. 2018 Jun 21;9(12):3271-3277. doi: 10.1021/acs.jpclett.8b01470. Epub 2018 Jun 5.

Abstract

Dissociative chemisorption of O on the Al(111) surface represents an extensively studied prototype for understanding the interaction between O and metal surfaces. It is well known that the experimentally observed activation barrier for O dissociation is not captured by conventional density functional theory. The interpretation of this barrier as a result of spin transitions along the reaction path has been challenged by recent embedded correlated wave function (ECW) calculations that naturally yield an adiabatic barrier. However, the ECW calculations have been limited to a static analysis of the reaction pathways and have not yet been tested by dynamics simulations. We present a global six-dimensional potential energy surface (PES) for this system parametrized with ECW data points. This new PES provides a reasonable description of the site-specific and orientation-dependent activation barriers. Quasi-classical trajectory calculations on this PES semiquantitatively reproduce both the observed translational energy dependence of the sticking probability and steric effects with aligned O molecules.

摘要

氧在Al(111)表面的解离化学吸附是理解氧与金属表面相互作用的一个经过广泛研究的原型。众所周知,传统密度泛函理论无法捕捉到实验观测到的氧解离活化能垒。最近的嵌入相关波函数(ECW)计算自然地产生了一个绝热能垒,这对将该能垒解释为沿反应路径自旋跃迁的结果提出了挑战。然而,ECW计算仅限于对反应路径的静态分析,尚未通过动力学模拟进行检验。我们用ECW数据点参数化给出了该体系的一个全局六维势能面(PES)。这个新的PES合理地描述了位点特异性和取向依赖性活化能垒。基于此PES的准经典轨迹计算半定量地再现了观测到的粘附概率的平动能依赖性以及与排列的氧分子相关的空间效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/48b3/6025882/a42dbf9cb2ad/jz-2018-01470g_0001.jpg

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