The PrimatQ Lab focuses on developing next-generationsimulation techniques that integrate first-principles calculations, artificial intelligence, and quantum theory. Our core research explores the geometric and electronic properties of 2D materials and heterostructures,the formation and dynamics of defects, and surface catalytic reactions at the atomic scale. We also implement deep learning and data-driven modeling to build automated workflows for materials screening and property prediction, enhancing both accuracy and computational efficiency. Our research spans applications in energy conversion, nanoelectronics, and quantum information science, aiming to establish a predictive, multiscale theoretical framework that accelerates the discovery and design of emerging functional materials. Research journal publication（From Phys.org）：Precision-shaped Cu₂O crystals unlock new potential for clean energy catalysts
