Energy crisis and environmental pollution are the major problems of human survival and development. Photocatalytic technology can effectively use solar energy and is prospective to solve the above-mentioned problems. Carbon nitride is a two-dimensional polymer material with a graphite-like structure. It has good physical and chemical stabilities, unique chemical and electronic energy band structures, and is widely used in the field of photocatalysis. Graphitic carbon nitride has a conjugated large π bond structure, which is easier to be modified with other compounds. thereby the surface area and visible light absorption range of carbon nitride-based photocatalytic composites can be insignificantly increased, and interface electron transmission and corresponding photogenerated carriers separation of streams are simultaneously promoted. Therefore, the present study systematically introduced the basic catalytic principles, preparation and modification methods, characterization and calculation simulation of carbon nitride-based photocatalytic composite materials, and their application in wastewater treatment. We also summarized their application in wastewater treatment with the aid of artificial intelligence tools. This review summarized the frontier technology and future development prospects of graphite phase carbon nitride photocatalytic composites, which provide a theoretical reference for wastewater purification.

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The photocatalytic degradation of antibiotics requires a good separation efficiency of photogenerated electron-hole pairs and a wide visible light absorption range. Current studies have discussed the successful preparation of ferroferric oxide/graphite carbon nitride/reduced graphene oxide (Fe3O4/g-C3N4/rGO). The phase structure and morphology of Fe3O4/g-C3N4/rGO composites were characterized by XRD, HR-TEM, SEM and EDS. The obtained composites were used to degrade tetracycline hydrochloride to evaluate its photocatalytic activity. The effects of four variables on the degradation of tetracycline hydrochloride were analyzed by the response surface method and artificial intelligence (gradient regression tree, random forest, artificial neural network, etc.). The results showed that the graphite carbon nitride in the catalyst maintained its original structure and that the photocatalytic activity was significantly improved. The degradation rate of tetracycline hydrochloride was 86.7%. The artificial neural network combined with a genetic algorithm was the best model for predicting the degradation of tetracycline hydrochloride by nanocomposites. The degradation of tetracycline hydrochloride was in accordance with the pseudosecond-order kinetic model. The proposed photocatalytic mechanism study indicated that ∙O2− and ∙OH radicals are the foremost reactive species that have vital roles in the photodegradation process. This finding provides a theoretical reference for the photocatalytic degradation of antibiotics (or analogous pollutants) in wastewater.