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  5. Development of Highly-Active Catalysts toward Oxygen Reduction by Controlling the Shape and Composition of Pt–Ni Nanocrystals

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Article
en
2023

Development of Highly-Active Catalysts toward Oxygen Reduction by Controlling the Shape and Composition of Pt–Ni Nanocrystals

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en
2023
Vol 15 (42)
Vol. 15
DOI: 10.1021/acsami.3c10514

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Younan Xia
Younan Xia

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Minghao Xie
Min Shen
Ruhui Chen
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Abstract

Electrocatalysts comprised of Pt–Ni alloy nanocrystals have garnered substantial attention due to their outstanding performance in catalyzing the oxygen reduction reaction (ORR). Herein, we present the synthesis of Pt–Ni nanocrystals with a variety of controlled shapes and compositions in an effort to investigate the impact of the Ni content on the formation of {111} facets and thereby the ORR activity. By completely excluding O2 from the reaction system, we could prevent the generation of Ni(OH)2 on the surface of the nanocrystals and thereby achieve a linear relationship between the atomic ratio of Pt to Ni in the nanocrystals and the feeding ratio of the precursors. The atomic ratio of Pt to Ni in the Pt–Ni nanocrystals was tunable within the range of 1.2–7.2, while their average sizes were kept around 9 nm in terms of edge length. In addition, a quantitative correlation between the area ratio of {111} to {100} facets and the feeding ratio of Pt(II) to Ni(II) was obtained by adjusting the mole fraction of the Ni(II) precursor in the reaction mixture. For the catalysts comprising octahedral nanocrystals, their specific ORR activities exhibited a positive correlation with the Pt/Ni atomic ratio. After the accelerated durability test, both specific and mass activity displayed a volcano-type trend with a peak value at a Pt/Ni atomic ratio of 1.6.

How to cite this publication

Minghao Xie, Min Shen, Ruhui Chen, Younan Xia (2023). Development of Highly-Active Catalysts toward Oxygen Reduction by Controlling the Shape and Composition of Pt–Ni Nanocrystals. , 15(42), DOI: https://doi.org/10.1021/acsami.3c10514.

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Publication Details

Type

Article

Year

2023

Authors

4

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsami.3c10514

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