Information from the abstract
Among the other carbon nitrides, graphitic carbon nitride (g-C₃N₄) is an economically viable, chemically stable, and thermally stable visible light-driven photocatalyst with an appropriate band gap of ∼2.7 eV. However, its application is curtailed because of fast recombination of charge carriers generated by light and low efficiency of capturing visible light photons. To address these limitations, hybrid structures of MXenes and g-C₃N₄, particularly with Ti₃C₂ MXene, have been gaining significant attention. The interfacial interaction of these hybrids is strong, which facilitates the efficient spatial charge separation, and numerous active sites, commonly arranged in a 2D/2D configuration including Type I, Type II, Schottky, and Z-scheme structures. This review summarizes the synthesis strategies, structural engineering, for the MXene/g-C₃N₄ hybrid systems composites, focusing mainly on self-assembly techniques that can afford the intimate hetero0interfaces. It discusses the synergistic benefits from the excellent metallic conductivity of the Ti₃C₂ MXene and high ability to absorb visible light of g-C₃N₄. Photocatalytic degradation of organic pollutants, hydrogen production by water splitting, and the photo-reduction of CO₂ to valuable fuels are the key applications that are discussed. New applications like self-cleaning surfaces and oil-water separation are also included. Overall, the photocatalytic performance of MXene/g-C₃N₄ hybrids is characterized by high efficiency, good stability, and reusability, which demonstrates their potential for sustainable energy generation and environmental sustainability with great promise for practical implementation in the near future. Furthermore, current review also described the emerging role of machine learning (ML) and artificial intelligence (AI) in selection of catalyst properties, reaction parameter and optimization. Finally, current challenges, quantum efficiency improvement, continuing reduction in charge carrier recombination, knowledge gaps, and future research directions are discussed, to make it viable for real-world applications.
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Related topics: MXene and MAX Phase Materials · Advanced Memory and Neural Computing · Boron and Carbon Nanomaterials Research
Thai researcher and institutional participation
Muhammad Qasim · Walailak University
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