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Issue 10, 2018
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Operando X-ray spectroscopic tracking of self-reconstruction for anchored nanoparticles as high-performance electrocatalysts towards oxygen evolution

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Abstract

Exploring high-performance electrocatalysts for the oxygen evolution reaction (OER) is pivotal for renewable energy storage and conversion. The surface self-reconstruction during the OER is considered as the key of highly active catalysts, whereas identifying the local electronic and geometric structure of the reconstruction-derived components is challenging. Herein, an in situ exsolution method towards the typical LaCo0.8Fe0.2O3−δ perovskite is developed to obtain a new type of lanthana-anchored CoFe catalyst. The optimized catalyst exhibits a low overpotential of 293 mV to reach the current density of 10 mA cm−2 in 0.1 M KOH. Most importantly, operando X-ray absorption spectroscopy (XAS) measurements demonstrate that the CoFe species in the catalyst are nearly transformed into unique (Co/Fe)O(OH) with a definite coordination-unsaturated structure under electrochemical conditions, which actually contributes to this superior performance. Moreover, the presence of the lanthana support promotes this transformation. Our work not only suggests a facile reconstructive strategy to dramatically enhance the OER activity of perovskite oxides in alkaline media, but also unravels the fine structure of true active sites through operando X-ray spectroscopic tracking.

Graphical abstract: Operando X-ray spectroscopic tracking of self-reconstruction for anchored nanoparticles as high-performance electrocatalysts towards oxygen evolution

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Publication details

The article was received on 15 Mar 2018, accepted on 03 Jul 2018 and first published on 06 Jul 2018


Article type: Paper
DOI: 10.1039/C8EE00773J
Citation: Energy Environ. Sci., 2018,11, 2945-2953
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    Operando X-ray spectroscopic tracking of self-reconstruction for anchored nanoparticles as high-performance electrocatalysts towards oxygen evolution

    S. Song, J. Zhou, X. Su, Y. Wang, J. Li, L. Zhang, G. Xiao, C. Guan, R. Liu, S. Chen, H. Lin, S. Zhang and J. Wang, Energy Environ. Sci., 2018, 11, 2945
    DOI: 10.1039/C8EE00773J

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