Descriptor-driven design of carbon nitride for visible light photocatalysis

Photocatalysis utilizing carbon nitride (CN) based photocatalysts presents an eco-friendly solution to energy challenges. Despite progress in enhancing CN performance, targeted design for specific applications remains challenging due to the complex feature-activity relationships. A computation-assisted strategy is proposed to explore multidimensional correlations between electronic properties and photoactivity in CNs for various applications, identifying d/p-band centers and effective mass as key descriptors for CN photocatalyst design. Specifically, the d-band center of the co-catalyst (Pt) correlates with H* dissociation energy, serving as a descriptor for designing hydrogen evolution reaction (HER) photocatalysts: the N-C p-band center difference, closely linking to O₂ adsorption and activation, emerges as a valuable indicator for H₂O₂ generation. These descriptors guide CN photocatalyst design through defect engineering, leading to a 6.7-fold increase in HER and 24.1-fold boost in H₂O₂ generation compared to pristine CN. Mechanistic analyses further reveal deeper structure-performance relationships, illustrating the influence of CN local structure on the stability of critical intermediates and the energy barriers of rate-limiting steps. By integrating computational and experimental methods, this study establishes a robust framework for the rational design of CN-based photocatalysts. This approach has significant potential for extension to other photocatalytic systems, offering broader applications in energy and environmental fields.