Li, XuyingMai, HaoxinTakata, TsuyoshiCox, NicholasLi, QiLu, JunlinWen, XiaomingMayes, Edwin L.H.Russo, Salvy P.Hisatomi, TakashiDomen, KazunariChen, DehongCaruso, Rachel A.2025-12-162025-12-161463-9262ORCID:/0000-0002-7815-6115/work/189581447https://hdl.handle.net/1885/733794869Photocatalysis 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.This research was supported by Australian Research Council (ARC) Discovery Projects (DP180103815 and DP220100945). This work was also supported by computational resources provided by the National Computational Infrastructure (NCI) under the National Computational Merit Allocation Scheme 2025 (NCMAS 2025). The authors acknowledge the RMIT University Microscopy and Microanalysis Facility (RMMF) for scientific and technical assistance. We thank the technical officers in the STEM College of RMIT University for associated technical support. The authors also acknowledge the support of the ARC under the Centre of Excellence scheme (project number CE170100026).13enPublisher Copyright: © 2025 The Royal Society of Chemistry.2025-04-1010.1039/d5gc00353a105003067597