Order of magnitude reduction in Joule heating of single molecular junctions between graphene electrodes.

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.