Breaking the Limitations of Activity and Stability in Powdered Materials for Oxygen Evolution Reaction: The Critical Role of Catalyst-Inducing Seeds
- 1. South China University of Technology
- 2. GuangDong Engineering Technology Research Center of Advanced Energy Storage Materials, Guangzhou 510640, PR China
- 3. Zhiyuan Research Institute, Hangzhou 310024, PR China
- 4. Hong Kong University of Science and Technology
- 5. California Institute of Technology
Abstract
Powdered catalysts are extensively employed in industrial-scale energy conversion devices but struggle with weak powder-substrate adhesion and inherent instability in gas-evolving and highly oxidative oxygen evolution reactions (OER). This work introduces an innovative strategy in which powdered materials serve a critical role as catalyst-inducing seeds to break these limitations. Specifically, powdered Ti2CTx MXene with anchored cobalt single atoms (Co-SAs) shows negligible catalytic activity on its own but serves as catalyst-inducing seeds, significantly enhancing the catalytic activity of the conductive FeNi substrate. Mechanistic studies demonstrate that Co-SAs accelerate the oxidation rate of Ti2CTx, leading to the micro-battery corrosion behavior between oxidized Co/Ti2CTx and FeNi alloy, which generates highly OER-active corrosion products tightly bonded to FeNi alloy, thereby enhancing catalytic activity and ensuring stability. The prepared porous electrode shows a low overpotential of 303 mV to deliver an ultra-high current density of 1000 mA cm−2 and maintains activity for 1200 hours under high current density conditions, rivaling advanced self-supporting electrodes. Moreover, replacing Co in Co/Ti2CTx with metals like Fe, Ni or Mn, yields comparable effects, suggesting the scalability of catalyst-inducing seeds. This approach breaks traditional limitations of powdered materials in OER, offering an effective pathway to engineer advanced catalytic electrodes.
Copyright and License
© 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Acknowledgement
This work was financially supported by the National Natural Science Foundation of China (No. 52101254), and Guangdong Basic and Applied Basic Research Foundation (2023B1515040011). C.B.M. and W.A.G. were supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Fuels from Sunlight Hub under Award Number DE-SC0021266.
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Additional details
- Office of Basic Energy Sciences
- Fuels from Sunlight Hub DE-SC0021266
- National Natural Science Foundation of China
- 52101254
- Accepted
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2024-11-03Accepted
- Available
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2024-11-04Published online
- Available
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2024-11-08Version of record
- Publication Status
- Published