Li Gen, Hu Bing-Zhong, Mao Wen-Hao, Yang Nuo, Lü Jing-Tao
School of Physics, Institute for Quantum Science and Engineering, and Wuhan National High Magnetic Field Center, Huazhong University of Science and Technology, Wuhan 430074, China.
State Key Laboratory of Cool Combustion, and School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
J Chem Phys. 2022 Nov 7;157(17):174303. doi: 10.1063/5.0118952.
Maintaining stability of single-molecular junctions (SMJs) in the presence of current flow is a prerequisite for their potential device applications. However, theoretical understanding of nonequilibrium heat transport in current-carrying SMJs is a challenging problem due to the different kinds of nonlinear interactions involved, including electron-vibration and anharmonic vibrational coupling. Here, we overcome this challenge by accelerating Langevin-type current-induced molecular dynamics using machine-learning potential derived from density functional theory. We show that SMJs with graphene electrodes generate an order of magnitude less heating than those with gold electrodes. This is rooted in the better phonon spectral overlap of graphene with molecular vibrations, rendering harmonic phonon heat transport being dominant. In contrast, in a spectrally mismatched junction with gold electrodes, anharmonic coupling becomes important to transport heat away from the molecule to surrounding electrodes. Our work paves the way for studying current-induced heat transport and energy redistribution in realistic SMJs.
在有电流流动的情况下保持单分子结(SMJs)的稳定性是其潜在器件应用的先决条件。然而,由于涉及多种非线性相互作用,包括电子 - 振动和非谐振动耦合,对载流单分子结中的非平衡热传输进行理论理解是一个具有挑战性的问题。在这里,我们通过使用从密度泛函理论导出的机器学习势来加速朗之万型电流诱导分子动力学,克服了这一挑战。我们表明,具有石墨烯电极的单分子结产生的热量比具有金电极的单分子结少一个数量级。这源于石墨烯与分子振动更好的声子谱重叠,使得谐波声子热传输占主导。相比之下,在与金电极光谱不匹配的结中,非谐耦合对于将热量从分子传输到周围电极变得很重要。我们的工作为研究实际单分子结中电流诱导的热传输和能量重新分布铺平了道路。