Importance Sampling for Equilibrium Properties in Non-Adiabatic Systems: Application to Anomalous Interfacial Charge Transfer

Interfacial charge transfer plays a significant rolein the performanceof optoelectronic devices. Compared with real-time non-adiabatic dynamicssimulations, statistical mechanics could obtain the equilibrium propertiesdirectly. We here present an importance sampling approach to calculatethe electron distribution at general interfaces. The configurationdistribution based on a series of reference potential energy surfacesis utilized to reweight the properties of interest. The high accuracy,precision, and efficiency of the new method are verified by comparingthe results of different sampling approaches and non-adiabatic dynamicssimulations. We find that numbers of states, electronic couplings,reorganization energies, and energetic disorders all have strong impactson the anomalous interfacial charge transfer across a high energybarrier. In addition, based on the data computed by importance samplingin relatively small but diverse systems, we propose an effective machinelearning approach to train artificial neural networks, which couldpredict the interfacial charge transfer in extremely large systems.Due to its high performance, our importance sampling method is promisingfor the statistical study of equilibrium properties in general non-adiabaticsystems.