A neural-network-like catalyst structure for the oxygen reduction reaction: carbon nanotube bridged hollow PtCo alloy nanoparticles in a MOF-like matrix for energy technologies
- Submitting institution
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Loughborough University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 2260
- Type
- D - Journal article
- DOI
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10.1039/c9ta06712d
- Title of journal
- Journal of Materials Chemistry A
- Article number
- -
- First page
- 19786
- Volume
- 7
- Issue
- 34
- ISSN
- 2050-7488
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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9
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper impacts the state of the art by improving fuel cell performance of a neural-network-like catalytic layer constructed via bionic design. It was selected as a HOT article by Journal of Materials Chemistry A in 2019. The demonstrated research strategy has been adopted widely in designing efficient catalysts for energy and environmental engineering in recent publications. It was selected by UKRI in case studies promoting the international impact of the collaborative research. It contributed to the further funding awards from the Royal Society/Newton Fund (NAF\R1\191294) and the MOST of China (G20190013008).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
