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  5. Surface‐Tailored Medium Entropy Alloys as Radically Low Overpotential Oxygen Evolution Electrocatalysts

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Article
en
2022

Surface‐Tailored Medium Entropy Alloys as Radically Low Overpotential Oxygen Evolution Electrocatalysts

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en
2022
Vol 18 (11)
Vol. 18
DOI: 10.1002/smll.202105611

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Ho Won Jang
Ho Won Jang

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Hoonkee Park
Jae Wung Bae
Tae Hyung Lee
+12 more

Abstract

Numerous studies have explored new materials for electrocatalysts, but it is difficult to discover materials that surpass the catalytic activity of current commercially available noble metal electrocatalysts. In contrast to conventional transition metal alloys, high-entropy alloys (HEAs) have immense potential to maximize their catalytic properties because of their high stability and compositional diversity as oxygen evolution reactions (OERs). This work presents medium-entropy alloys (MEAs) as OER electrocatalysts to simultaneously satisfy the requirement of high catalytic activity and long-term stability. The surface of MEA electrocatalyst is tailored to suit the OER via anodizing and cyclic voltammetry activation methods. Optimized electrical properties and hydrophilicity of the surface enable an extremely low overpotential of 187 mV for achieving the current density of 10 mA cm-2 alkaline media. Furthermore, a combined photovoltaic-electrochemical system with MEA electrocatalyst and a perovskite/Si tandem solar cell exhibits a solar-to-hydrogen conversion efficiency of 20.6% for an unassisted hydrogen generation system. These results present a new pathway for designing sustainable high efficiency water splitting cells.

How to cite this publication

Hoonkee Park, Jae Wung Bae, Tae Hyung Lee, Ik Jae Park, Changyeon Kim, Mi Gyoung Lee‬, Sol A Lee, Jin Wook Yang, Min‐Ju Choi, Sung Hyun Hong, Soo Young Kim, ‪Sang Hyun Ahn, Jin Young Kim, Hyoung Seop Kim, Ho Won Jang (2022). Surface‐Tailored Medium Entropy Alloys as Radically Low Overpotential Oxygen Evolution Electrocatalysts. , 18(11), DOI: https://doi.org/10.1002/smll.202105611.

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Publication Details

Type

Article

Year

2022

Authors

15

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/smll.202105611

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