Dissociative chemisorption of methane on Ni(111) using a chemically accurate fifteen dimensional potential energy surface,Physical Chemistry Chemical Physics

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Dissociative chemisorption of methane on Ni(111) using a chemically accurate fifteen dimensional potential energy surface
Physical Chemistry Chemical Physics ( IF 2.9 ) Pub Date : 2017-10-31 00:00:00 , DOI: 10.1039/c7cp05993k
Xueyao Zhou _{1,

2,

3,

4} , Francesco Nattino _{5,

6,

7,

8,

9} , Yaolong Zhang _{1,

2,

3,

4} , Jun Chen _{10,

11,

12,

13,

14} , Geert-Jan Kroes _{5,

6,

7,

8,

9} , Hua Guo _{15,

16,

17,

18} , Bin Jiang _{1,

2,

3,

4}

Affiliation

Department of Chemical Physics
University of Science and Technology of China
Hefei
China
Leiden Institute of Chemistry
Leiden University
Gorlaeus Laboratories
P.O. Box 9502
2300 RA Leiden
Collaborative Innovation Center of Chemistry for Energy Materials (iChEM)
College of Chemistry and Chemical Engineering
Xiamen University
Xiamen
Fujian 361005
Department of Chemistry and Chemical Biology
University of New Mexico
Albuquerque
USA

A fifteen-dimensional global potential energy surface for the dissociative chemisorption of methane on the rigid Ni(111) surface is developed by a high fidelity fit of ∼200 000 DFT energy points computed using a specific reaction parameter density functional designed to reproduce experimental data. The permutation symmetry and surface periodicity are rigorously enforced using the permutation invariant polynomial-neural network approach. The fitting accuracy of the potential energy surface is thoroughly investigated by examining both static and dynamical attributes of CHD₃ dissociation on the frozen surface. This potential energy surface is expected to be chemically accurate as after correction for surface temperature effects it reproduces the measured initial sticking probabilities of CHD₃ on Ni(111) for various incidence conditions.

中文翻译：

甲烷在Ni（111）上的离解化学吸附使用化学精确的15维势能表面

通过使用特定的反应参数密度函数计算的〜200 000 DFT能量点的高保真度拟合，开发了用于在刚性Ni（111）表面上甲烷解离化学吸附的15维全局势能表面，该函数设计用于重现实验数据。使用置换不变多项式-神经网络方法严格执行置换对称性和表面周期性。通过检查CHD ₃在冰冻表面上的解离的静态和动态属性，彻底研究了势能表面的拟合精度。预期该势能表面在化学上是准确的，因为在校正了表面温度影响后，它会重现所测CHD _3的初始粘着概率在Ni（111）上用于各种入射条件。

更新日期：2017-11-22

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