Experimental and Theoretical Study of Multi-Quantum Vibrational Excitation: NO(v = 0鈫?,2,3) in Collisions with Au(111)
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- 作者：Kai Golibrzuch ; Alexander Kandratsenka ; Igor Rahinov ; Russell Cooper ; Daniel J. Auerbach ; Alec M. Wodtke ; Christof Bartels
- 刊名：The Journal of Physical Chemistry A
- 出版年：2013
- 出版时间：August 15, 2013
- 年：2013
- 卷：117
- 期：32
- 页码：7091-7101
- 全文大小：526K
- 年卷期：v.117,no.32(August 15, 2013)
- ISSN：1520-5215
文摘
We measured absolute probabilities for vibrational excitation of NO(v = 0) molecules in collisions with a Au(111) surface at an incidence energy of translation of 0.4 eV and surface temperatures between 300 and 1100 K. In addition to previously reported excitation to v = 1 and v = 2, we observed excitation to v = 3. The excitation probabilities exhibit an Arrhenius dependence on surface temperature, indicating that the dominant excitation mechanism is nonadiabatic coupling to electron鈥揾ole pairs. The experimental data are analyzed in terms of a recently introduced kinetic model, which was extended to include four vibrational states. We describe a subpopulation decomposition of the kinetic model, which allows us to examine vibrational population transfer pathways. The analysis indicates that sequential pathways (v = 0 鈫?1 鈫?2 and v = 0 鈫?1 鈫?2 鈫?3) alone cannot adequately describe production of v = 2 or 3. In addition, we performed first-principles molecular dynamics calculations that incorporate electronically nonadiabatic dynamics via an independent electron surface hopping (IESH) algorithm, which requires as input an ab initio potential energy hypersurface (PES) and nonadiabatic coupling matrix elements, both obtained from density functional theory (DFT). While the IESH-based simulations reproduce the v = 1 data well, they slightly underestimate the excitation probabilities for v = 2, and they significantly underestimate those for v = 3. Furthermore, this implementation of IESH appears to overestimate the importance of sequential energy transfer pathways. We make several suggestions concerning ways to improve this IESH-based model.