异质结
价(化学)
化学计量学
材料科学
催化作用
化学物理
金属
化学
物理化学
光电子学
生物化学
有机化学
冶金
作者
Siao Chen,Yurui Xue,Yang Gao,Han Wu,Si–Yi Chen,Yunhao Zheng,Yuliang Li
标识
DOI:10.1002/anie.202507269
摘要
Abstract Dynamic rearrangement of metal atoms at heterointerfaces by chemical bond conversion drives high efficiency electrocatalytic processes, which is a new concept in the field of electrocatalysis and a new discovery to directly improve catalytic activity. It is of great significance to explore transformative catalytic systems that directly control the interfacial structure and function of atomic composition. As an emerging 2D carbon allotrope featuring unique sp ‐ sp 2 co‐hybridization, graphdiyne (GDY) offers unprecedented advantages for heterointerface engineering. In particular, the uneven surface charge distribution of GDY, high distribution of active sites and customizable electronic structures provide unprecedented opportunities for the development of a new generation of catalytic systems. Here, we report a new idea to directly control the cooperative growth and drive metal atomic rearrangement on the interface of GDY/NiPd/GDY. The results of atomic‐resolution electron microscopy characterization revealed two unique interfacial phenomena: i) GDY‐induced massive dislocation formation within NiPd nanoalloys and ii) rearrangement of surface metal atoms from (111) to (200) facets. Detailed spectroscopic analysis further demonstrated the composition‐dependent evolution of elemental valence states and stoichiometric ratios. This atomic‐level restructuring establishes a charge‐redistribution network featuring non‐integer charge transfer, which improves the overall conductivity and intrinsic activity. What is even more encouraging is that this electrocatalytic olefin hydrogenation is carried out in an aqueous solution. The GDY/NiPd/GDY heterostructure achieves exceptional activity (turnover frequency: 6.8 s −1 ), stability (>5 cycles), and chemo‐selectivity (−100%), which is superior to traditional catalysts.
科研通智能强力驱动
Strongly Powered by AbleSci AI