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arXiv:2212.00518 (physics)
[Submitted on 1 Dec 2022 (v1) , last revised 18 Jan 2023 (this version, v2)]

Title: Efficient implementation and performance analysis of the independent electron surface hopping method for dynamics at metal surfaces

Title: 独立电子表面跳跃方法在金属表面动力学中的高效实现与性能分析

Authors:James Gardner, Daniel Corken, Svenja M. Janke, Scott Habershon, Reinhard J. Maurer
Abstract: Independent electron surface hopping (IESH) is a computational algorithm for simulating the mixed quantum-classical molecular dynamics of adsorbate atoms and molecules interacting with metal surfaces. It is capable of modelling the nonadiabatic effects of electron-hole pair excitations on molecular dynamics. Here we present a transparent, reliable, and efficient implementation of IESH, demonstrating its ability to predict scattering and desorption probabilities across a variety of systems, ranging from model Hamiltonians to full dimensional atomistic systems. We further show how the algorithm can be modified to account for the application of an external bias potential, comparing its accuracy to results obtained using the hierarchical quantum master equation. Our results show that IESH is a practical method for modelling coupled electron-nuclear dynamics at metal surfaces, especially for highly energetic scattering events.
Abstract: 独立电子表面跳跃(IESH)是一种用于模拟吸附原子和分子与金属表面相互作用的混合量子经典分子动力学的计算算法。 它能够对电子-空穴对激发的非绝热效应进行建模。 在这里,我们展示了一个透明、可靠且高效的IESH实现,证明了其在各种系统中预测散射和解离概率的能力,从模型哈密顿量到完整的维度原子系统。 我们进一步展示了如何修改该算法以考虑外部偏置势的应用,并将其准确性与使用分层量子主方程获得的结果进行比较。 我们的结果表明,IESH是一种在金属表面建模耦合电子-核动力学的实用方法,特别是在高能散射事件中。
Comments: 15 pages, 9 figures; added new performance data without hopping estimate; added CME results; clarified details in Appendix B
Subjects: Chemical Physics (physics.chem-ph)
Cite as: arXiv:2212.00518 [physics.chem-ph]
  (or arXiv:2212.00518v2 [physics.chem-ph] for this version)
  https://doi.org/10.48550/arXiv.2212.00518
arXiv-issued DOI via DataCite
Related DOI: https://doi.org/10.1063/5.0137137
DOI(s) linking to related resources

Submission history

From: James Gardner [view email]
[v1] Thu, 1 Dec 2022 14:12:52 UTC (867 KB)
[v2] Wed, 18 Jan 2023 10:28:18 UTC (1,295 KB)
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