Band structure engineering in porous g-C3N4 via tailoring surface carbon for enhanced photocatalytic hydrogen evolution

Abstract

Atomic-level regulation of graphitic carbon nitride (g-C3N4) is a promising approach to enhance its inherent photocatalytic performance by optimizing the electronic band structure and improving charge separation. Herein, we developed a novel strategy for synthesizing surface-carbon-modified porous ultrathin g-C3N4 nanosheets via a chemical vapor deposition (CVD) process. This method utilizes the endogenous gases from the pyrolysis of polyacrylonitrile (PAN) to simultaneously act as a carbon source for surface deposition and as an etchant to exfoliate bulk g-C3N4 into ultrathin nanosheets. By simply adjusting the CVD temperature, the degree of carbon modification was precisely controlled. The optimal sample (CNP550) exhibits a substantially increased specific surface area of 378.0 m²·g⁻¹ and a large pore volume of 8.6 cm³·g⁻¹. Benefiting from this unique structure and the carbon modification, the bandgap of g-C3N4 was narrowed from 2.87 eV to 1.94 eV, while the conduction band was shifted to a higher energy. These electronic modifications collectively led to a substantial enhancement in electron-hole separation efficiency. As a result, the CNP550 sample achieved an outstanding photocatalytic hydrogen evolution rate of 688.2 μmol·g⁻¹·h⁻¹ under visible light, which is 7.8 times higher than that of bulk g-C3N4, along with excellent long-term stability. This work offers a novel synergistic strategy for carbon doping and nanostructure engineering of ultrathin g-C3N4 nanosheets, providing an effective approach for bandgap tuning and the construction of high-performance photocatalysts for solar energy conversion.

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Article information

Article type
Paper
Submitted
15 Nov 2025
Accepted
03 Feb 2026
First published
08 Feb 2026

Nanoscale, 2026, Accepted Manuscript

Band structure engineering in porous g-C3N4 via tailoring surface carbon for enhanced photocatalytic hydrogen evolution

J. He, S. Ye, Z. He, Y. Chen, L. Chen, W. Ma, A. Li, F. Yang and S. Gao, Nanoscale, 2026, Accepted Manuscript , DOI: 10.1039/D5NR04835D

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