Spiering Paul, Meyer Jörg
Leiden Institute of Chemistry, Gorlaeus Laboratories , Leiden University , P.O. Box 9502, 2300 RA Leiden , The Netherlands.
J Phys Chem Lett. 2018 Apr 5;9(7):1803-1808. doi: 10.1021/acs.jpclett.7b03182. Epub 2018 Mar 27.
At present, molecular dynamics with electronic friction (MDEF) is the workhorse model to go beyond the Born-Oppenheimer approximation in modeling dynamics of molecules at metal surfaces. Concomitant friction coefficients can be calculated with either the local density friction approximation (LDFA) or orbital-dependent friction (ODF), which, unlike LDFA, accounts for anisotropy while relying on other approximations. Due to the computational cost of ODF, extensive high-dimensional MDEF trajectory calculations of experimentally measurable observables have hitherto only been performed based on LDFA. We overcome this limitation with a continuous neural-network-based representation. In our first application to the scattering of vibrationally excited H and D from Cu(111), we predict up to three times higher vibrational de-excitation probabilities with ODF than with LDFA. These results indicate that anisotropic electronic friction can be important for specific molecular observables. Future experiments can test for this "fingerprint" of different approximations underlying state-of-the-art MDEF.
目前，带电子摩擦的分子动力学（MDEF）是超越玻恩-奥本海默近似来模拟金属表面分子动力学的主力模型。伴随摩擦系数可以通过局部密度摩擦近似（LDFA）或轨道相关摩擦（ODF）来计算，与LDFA不同，ODF在依赖其他近似的同时考虑了各向异性。由于ODF的计算成本，迄今为止，基于LDFA仅对实验可测量可观测量进行了广泛的高维MDEF轨迹计算。我们用基于连续神经网络的表示克服了这一限制。在我们首次应用于振动激发的H和D从Cu(111)的散射中，我们预测ODF的振动去激发概率比LDFA高多达三倍。这些结果表明，各向异性电子摩擦对于特定分子可观测量可能很重要。未来的实验可以检验这种不同近似的“指纹”，其是当前先进MDEF的基础。
