Reassessing structural models of graphitic carbon nitride for reliable photocatalytic predictions

Materials Advances 2026 Open access

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Authors: Gbemi Abass, Adnan Ahmad, Cheng Yang, Yun Liu, Terry J. Frankcombe
DOI: 10.1039/d6ma00065g
Cited by: 4
References: 49

Abstract

Graphitic carbon nitride (g-C 3 N 4 ) must be modelled as a layered material that has buckled layers, not flat, or else calculated doping and photophysical properties are fundamentally incorrect.

Fields of Study & Subjects

Advanced Photocatalysis Techniques TiO2 Photocatalysis and Solar Cells Machine Learning in Materials Science

Publication details

Journal / source
Materials Advances
Publisher
Royal Society of Chemistry (RSC)
Volume
7
Issue
8
Pages
4234–4247
Publication date
1 January 2026
Language
EN