Computational modeling guided design of metal-organic frameworks for photocatalysis - a mini review

Metal-organic frameworks (MOFs) are a class of materials that have a tunable porous structure and an ultrahigh surface area, which are quite active in photocatalytic water splitting and CO2 reduction. Some promising MOFs with various metal nodes are summarized in detail under visible light irradiation, demonstrating desired CO2 photoreduction and H2 generation efficiency. In the investigation of photocatalytic efficiency, computational modeling is critical. When it comes to band alignment from ground state calculation, the band edge positions are tailored to achieve the best photocatalytic performance by substituting with different groups and incorporating different metal centers. Although excited state calculation presents some difficulties, electronic properties can be adjusted by structural degrees of flexibility and different compositions based on density functional theory. This review will provide a concise overview of a diverse range of MOFs with various metal centers and incorporated ligands for photocatalysis. Based on computational modeling, the band gap of MOFs has excellent tunability. By changing the metal center and partially substituting ligands, the ideal band gap and electronic properties can be obtained, resulting in increased photocatalytic activity. Such modeling analysis may also play an important role in designing MOFs for photocatalytic applications, which warrants additional research attention in the improvement of photocatalytic performance. Metal-organic frameworks (MOFs) are porous materials used in photocatalysis. Their structure is optimized using computational modeling. This review emphasizes the role of computational design in enhancing MOF efficiency.