Lin-Zhi Zhang

Machine learning prediction of frontier orbital energies in graphene and silicon carbide quantum dots

This work addresses a critical gap in data-driven modeling of low-dimensional quantum materials by curating a dataset of 254 functionalized and doped graphene and silicon carbide quantum dots with DFT-computed HOMO and LUMO energies, establishing a foundation for high-throughput screening and inverse design of quantum...