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Hard X-ray Photoelectron Spectroscopy Probing Fe Segregation during the Oxygen Evolution Reaction

X射线光电子能谱 材料科学 氧气 析氧 X射线光谱学 光谱学 X射线 分析化学(期刊) 化学工程 物理化学 光学 环境化学 电极 化学 物理 有机化学 量子力学 工程类 电化学
作者
Filippo Longo,P.J. Lloreda-Jurado,Jorge Gil‐Rostra,Agustı́n R. González-Elipe,F. Yubero,Sabrina L. J. Thomä,A. Neels,Andreas Borgschulte
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:16 (43): 59516-59527 被引量:1
标识
DOI:10.1021/acsami.4c11902
摘要

NiFe electrocatalysts are among the most active phases for water splitting with regard to the alkaline oxygen evolution reaction (OER). The interplay between Ni and Fe, both at the surface and in the subsurface of the catalyst, is crucial to understanding such outstanding properties and remains a subject of debate. Various phenomena, ranging from the formation of oxides/(oxy)hydroxides to the associated segregation of certain species, occur during the electrochemical reactions and add another dimension of complexity that hinders the rational design of electrodes for water splitting. In this work, we have developed the procedure for the quantification of chemical depth profiling by XPS/HAXPES measurements and applied it to two NiFe electrodes with different porosities. The main outcome of this study is related to the surface reconstruction of the electrodes during the OER, followed at two different depths by means of X-ray photoelectron spectroscopy. We find that Fe initially segregates at the surface when exposed to ambient conditions, resulting in the formation of an inactive FeOx phase. In addition, the porosity of the catalyst plays a significant role in the segregation process and thus in the performance of the electrode. In particular, the higher porosity of the nanostructured sample is responsible for a more pronounced diffusion of Fe from the subsurface to the surface with a more effective suppression of the activity of the Ni1–xFexOOH phase. These results highlight the importance of the fact that the chemical state of the surface of a multielement system is a snapshot in time, dependent on both external parameters, such as the applied potential and the adjacent electrolyte, and the underlying bulk properties accessible with HAXPES.
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