NiFe Nanoparticle Nest Supported on Graphene as Electrocatalyst for Highly Efficient Oxygen Evolution Reaction
Abstract
Abstract Designing cost‐efffective electrocatalysts for the oxygen evolution reaction (OER) holds significant importance in the progression of clean energy generation and efficient energy storage technologies, such as water splitting and rechargeable metal–air batteries. In this work, an OER electrocatalyst is developed using Ni and Fe precursors in combination with different proportions of graphene oxide. The catalyst synthesis involved a rapid reduction process, facilitated by adding sodium borohydride, which successfully formed NiFe nanoparticle nests on graphene support (NiFe NNG). The incorporation of graphene support enhances the catalytic activity, electron transferability, and electrical conductivity of the NiFe‐based catalyst. The NiFe NNG catalyst exhibits outstanding performance, characterized by a low overpotential of 292.3 mV and a Tafel slope of 48 mV dec −1 , achieved at a current density of 10 mA cm − 2 . Moreover, the catalyst exhibits remarkable stability over extended durations. The OER performance of NiFe NNG is on par with that of commercial IrO 2 in alkaline media. Such superb OER catalytic performance can be attributed to the synergistic effect between the NiFe nanoparticle nests and graphene, which arises from their large surface area and outstanding intrinsic catalytic activity. The excellent electrochemical properties of NiFe NNG hold great promise for further applications in energymore »
- Authors:
-
- School of Mechanical and Materials Engineering Washington State University Pullman WA 99164 USA
- Department of Chemistry Washington State University Pullman WA 99164 USA
- School of Chemical, Biological, and Environmental Engineering Oregon State University Corvallis OR 97331 USA
- Department of Chemistry University of California Irvine Irvine CA 92697 USA
- Department of Nanoengineering University of California San Diego La Jolla CA 92093 USA
- Irvine Materials Research Institute (IMRI) Department of Physics and Astronomy Department of Materials Science and Engineering University of California Irvine Irvine CA 92697 USA
- The Gene and Linda Voiland School of Chemical Engineering and Bioengineering Washington State University Pullman WA 99164 USA
- School of Mechanical and Materials Engineering Washington State University Pullman WA 99164 USA, Department of Nanoengineering University of California San Diego La Jolla CA 92093 USA
- School of Mechanical and Materials Engineering Washington State University Pullman WA 99164 USA, Department of Chemistry Washington State University Pullman WA 99164 USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 2222494
- Alternate Identifier(s):
- OSTI ID: 2228336
- Grant/Contract Number:
- DE‐AC02‐06CH11357
- Resource Type:
- Published Article
- Journal Name:
- Small
- Additional Journal Information:
- Journal Name: Small; Journal ID: ISSN 1613-6810
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- Germany
- Language:
- English
Citation Formats
Lyu, Zhaoyuan, Yu, Sheng, Wang, Maoyu, Tieu, Peter, Zhou, Jiachi, Shi, Qiurong, Du, Dan, Feng, Zhenxing, Pan, Xiaoqing, Lin, Hongfei, Ding, Shichao, Zhang, Qiang, and Lin, Yuehe. NiFe Nanoparticle Nest Supported on Graphene as Electrocatalyst for Highly Efficient Oxygen Evolution Reaction. Germany: N. p., 2023.
Web. doi:10.1002/smll.202308278.
Lyu, Zhaoyuan, Yu, Sheng, Wang, Maoyu, Tieu, Peter, Zhou, Jiachi, Shi, Qiurong, Du, Dan, Feng, Zhenxing, Pan, Xiaoqing, Lin, Hongfei, Ding, Shichao, Zhang, Qiang, & Lin, Yuehe. NiFe Nanoparticle Nest Supported on Graphene as Electrocatalyst for Highly Efficient Oxygen Evolution Reaction. Germany. https://doi.org/10.1002/smll.202308278
Lyu, Zhaoyuan, Yu, Sheng, Wang, Maoyu, Tieu, Peter, Zhou, Jiachi, Shi, Qiurong, Du, Dan, Feng, Zhenxing, Pan, Xiaoqing, Lin, Hongfei, Ding, Shichao, Zhang, Qiang, and Lin, Yuehe. Mon .
"NiFe Nanoparticle Nest Supported on Graphene as Electrocatalyst for Highly Efficient Oxygen Evolution Reaction". Germany. https://doi.org/10.1002/smll.202308278.
@article{osti_2222494,
title = {NiFe Nanoparticle Nest Supported on Graphene as Electrocatalyst for Highly Efficient Oxygen Evolution Reaction},
author = {Lyu, Zhaoyuan and Yu, Sheng and Wang, Maoyu and Tieu, Peter and Zhou, Jiachi and Shi, Qiurong and Du, Dan and Feng, Zhenxing and Pan, Xiaoqing and Lin, Hongfei and Ding, Shichao and Zhang, Qiang and Lin, Yuehe},
abstractNote = {Abstract Designing cost‐efffective electrocatalysts for the oxygen evolution reaction (OER) holds significant importance in the progression of clean energy generation and efficient energy storage technologies, such as water splitting and rechargeable metal–air batteries. In this work, an OER electrocatalyst is developed using Ni and Fe precursors in combination with different proportions of graphene oxide. The catalyst synthesis involved a rapid reduction process, facilitated by adding sodium borohydride, which successfully formed NiFe nanoparticle nests on graphene support (NiFe NNG). The incorporation of graphene support enhances the catalytic activity, electron transferability, and electrical conductivity of the NiFe‐based catalyst. The NiFe NNG catalyst exhibits outstanding performance, characterized by a low overpotential of 292.3 mV and a Tafel slope of 48 mV dec −1 , achieved at a current density of 10 mA cm − 2 . Moreover, the catalyst exhibits remarkable stability over extended durations. The OER performance of NiFe NNG is on par with that of commercial IrO 2 in alkaline media. Such superb OER catalytic performance can be attributed to the synergistic effect between the NiFe nanoparticle nests and graphene, which arises from their large surface area and outstanding intrinsic catalytic activity. The excellent electrochemical properties of NiFe NNG hold great promise for further applications in energy storage and conversion devices.},
doi = {10.1002/smll.202308278},
journal = {Small},
number = ,
volume = ,
place = {Germany},
year = {Mon Nov 27 00:00:00 EST 2023},
month = {Mon Nov 27 00:00:00 EST 2023}
}
https://doi.org/10.1002/smll.202308278
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