Z-scheme metal organic framework/Ag@AgCl heterojunction photocatalysts with elevated photocatalytic N2 fixation activity
Source abstract
Abstract
As one of the most consumed chemical reagents, ammonia (NH 3) has a wide range of applications in many fields. The demand for ammonia may continue to increase with the advancement of technology and the acceleration of industrialization. The traditional high energy consumption and high pollution ammonia synthesis methods (Haber-Bosch) need to be optimized and improved to reduce environmental pollution and energy dependence. In this work, a series of Z-scheme NM/Ag@AgCl heterojunctions were prepared as catalysts for the research of photocatalytic nitrogen fixation. By in-situ photodeposition, Ag@AgCl was uniformly distributed on the NM surface, and the interfaces of different substances were tightly bonded. The SPR effect that generated by Ag nanoparticles significantly enhanced the light energy absorption performance of heterojunction materials. In the ESR spectra, the signal peak intensity of NM/Ag@AgCl was higher than that of NM under light condition. Constructing of heterojunction was beneficial to the formation of Ti 3+. The strong built-in electric field among NM and AgCl promoted the generation of Z-scheme heterojunction. NM/Ag@AgCl had sufficient redox potential to overcome thermodynamic barriers and drive the catalytic reaction. Without adding any sacrificial reagent, the ammonia production of NM/Ag@AgCl-3 reached 76.7 µmol g −1 h −1 under full spectrum radiation. The rate of ammonia formation of NM/Ag@AgCl was almost seven times than that of NM. The synergistic effect between NM and Ag@AgCl optimized the photogenerated carrier separation path. This work provided a new vision for the practical application of efficient photocatalytic N 2 reduction.
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Research context
OpenAlex topics: Advanced Photocatalysis Techniques · Metal-Organic Frameworks: Synthesis and Applications · Covalent Organic Framework Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (38)
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