Exploring the intrinsic relationship between defects in g-C₃N₄ and the enhancement of photogenerated carrier dynamics and photocatalytic performance

It is crucial to elucidate the intrinsic relationship between defects in g-C₃N₄ (pristine graphitic carbon nitride, here onwards bare carbon nitride-BCN) and the enhancement of photogenerated carrier dynamics and photocatalytic performance. Three types of defective g-C₃N₄ are prepared by defect engineering, called CVCN (carbon vacancies containing carbon nitride), NVCN (nitrogen vacancies containing carbon nitride), and OBCN (oxygen doped bulk carbon nitride). Various characterization techniques are employed to examine the materials' crystalline structure, chemical bonds, surface area, pore properties, light response, carrier recombination, vacancy/doping types, and carrier mobility. Ab initio calculations via VASP further elucidated band structure and charge distribution. Visible light-assisted Rhodamine B (RhB) degradation and hydrogen peroxide production experiments revealed that defect engineering significantly enhanced the photocatalytic degradation capacity of g-C₃N₄, with OBCN showing the highest RhB degradation rate which is 6.26 times higher than that of BCN (bulk carbon nitride), but suffering from photo-corrosion and its main reactive substances are h+ and ·O₂⁻; while NVCN exhibited the best hydrogen peroxide production capacity which is 1.83 times higher than that of BCN, the main active species is ·O₂⁻. Through the Vienna Ab initio Simulation Package software (VASP), the projection enhanced wave method is used to model and analyze the first principles calculation of the band structure of the samples and the change of elemental differential charge. The occurrence of defects slightly modulated the energy band structure of the photocatalyst, significantly inhibited the recombination phenomenon of photogenerated carriers, promoted the separation of photogenerated carriers, and ultimately improved the photocatalytic activity. Copyright © 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.