In Situ Identification of Dynamic Active Sites in the Electrocatalytic Nitrate Reduction Reaction

化学 硝酸盐 原位 还原(数学) 鉴定(生物学) 氧化还原 无机化学 有机化学 生态学 几何学 数学 生物
作者
Yong Zhao,Shuang Gao,Xiangyu Chen,Yue Liu,Mengjuan Zhang,Yifei Liu,Jianxin Kang,Tianqi Guo,Yuandong Niu,Lin Guo
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
卷期号:147 (35): 31722-31730 被引量:22
标识
DOI:10.1021/jacs.5c08371
摘要

Deciphering the spatiotemporal evolution of catalytic active sites under operational conditions is pivotal for establishing precise design principles in electrocatalysis. However, conventional electrochemical characterization techniques, which are limited in correlating physical topographical features with chemical activity, fundamentally obstruct the linkage between nanoscale structural and macroscopic activity descriptors. To address this challenge, an integrated operando electrochemical atomic force microscopy–scanning electrochemical microscopy platform was implemented, enabling simultaneous nanoscale tracking of the topographic reorganization and local activity distribution during the nitrate reduction reaction. Morphological analysis revealed that the amorphous SnO2 catalyst undergoes dynamic surface restructuring with an increase in roughness of up to 59.0% during catalysis, while operando current mapping confirmed that these roughened regions exhibited ∼100-fold enhancement in NH3 production activity compared to basal planes. Height profiling demonstrated that amorphous catalysts undergo ∼60% greater thickness reduction than crystalline counterparts during activation, constructing a dual-functional architecture with surface-exposed highly active Sn(II) sites and subsurface Sn(0) enabling rapid electron transport. These findings provided direct experimental evidence of electrochemically driven defect proliferation in amorphous catalysts, which synergistically contributes to NH3 yield several times higher than those of crystalline benchmarks, pointing to one of the best Sn-based catalysts. The developed correlative operando imaging strategy established a generalized paradigm for resolving transient catalytic dynamics across material systems with direct applicability to NO3RR optimization and emergent electrocatalytic processes.
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