化学
连接器
多元统计
还原(数学)
多元分析
金属
金属有机骨架
组合化学
有机化学
统计
吸附
几何学
数学
计算机科学
操作系统
作者
Ya Yin,Shijia Feng,Xinyu Xu,Yifan Liu,Youcong Li,Lei Gao,Xiao‐Cheng Zhou,Jiahao Dong,Yulun Wu,Jian Su,Jing‐Lin Zuo,Shuai Yuan,Jia Zhu
摘要
Photosensitization is a powerful approach for enhancing the photocatalyst performance by improving light absorption, energy transfer, and charge separation. However, achieving high efficiency requires precise control over photosensitizers, catalytic centers, and their interactions, which remain challenging in heterogeneous systems. Herein, we develop multivariate zirconium metal-organic frameworks (MOFs) with mixing linkers and tunable defects that enable unprecedented control over photosensitizers, catalytic centers, and their ratios, creating an efficient platform for CO2 reduction. These MOFs integrate triphenylamine, phenoxazine, or phenothiazine-based linkers as photosensitizers and metal porphyrin linkers (metal = Fe, Co, Ni, and Zn) as CO2 reduction catalytic centers. Furthermore, the defect tolerance of robust Zr6 nodes allows for a systematic variation in linker ratios by introducing missing linker defects. By fine-tuning the photosensitizers, catalytic metal centers, and their ratios, we achieved an optimized photocatalyst with CO2-to-CO reduction rates of 247.8 μmol gcat.-1 h-1, representing a 17-fold enhancement over homogeneous analogues. Transient spectra and density functional theory calculations reveal the critical role of the framework structure in promoting efficient intrareticular energy transfer and charge separation. This study highlights the unique advantage of MOF platforms in the multivariate tuning of photocatalysts, paving the way for advanced artificial photosynthetic systems.
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