In an article recently published in the journal ACS Applied Materials & Interfaces, using machine learning (ML) and Wannier analysis, an effective divide-and-conquer strategy is proposed to develop Hamiltonian of the system. Study: All-Atom Nonadiabatic Dynamics Simulation of Hybrid Graphene Nanoribbons Based on Wannier Analysis and Machine Learning. Several essential excitons and electron dynamic mechanisms, such as charge carrier movement, relaxing and diffusing excitons, segregation of electrons and holes, and recombination, are critical aspects in photovoltaic conversion devices, including solar panels, field-effect semiconductors, and LEDs. The dynamics of excitons and electrons are closely related to nuclear movements in these circumstances, and hence all fall under the framework of diabatic dynamics. In general, traditional molecular dynamics does not describe fundamental quantum phenomena, but pure quantum dynamics has enormous processing requirements when a significant number of degrees of freedom (DOFs) are concerned.