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Cited by 724

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Polyelectrolyte Functionalized Carbon Nanotubes as Efficient Metal-free Electrocatalysts for Oxygen Reduction

Wang, Shuangyin, Yu, Dingshan, Dai, Liming·2011·Journal of the American Chemical Society
DOI 10.1021/ja1112904
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Abstract

Having a strong electron-withdrawing ability, poly(diallyldimethylammonium chloride) (PDDA) was used to create net positive charge for carbon atoms in the nanotube carbon plane via intermolecular charge transfer. The resultant PDDA functionalized/adsorbed carbon nanotubes (CNTs), either in an aligned or nonaligned form, were demonstrated to act as metal-free catalysts for oxygen reduction reaction (ORR) in fuel cells with similar performance as Pt catalysts. The adsorption-induced intermolecular charge-transfer should provide a general approach to various carbon-based efficient metal-free ORR catalysts for oxygen reduction in fuel cells, and even new catalytic materials for applications beyond fuel cells.

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Citations

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Show all 3 references

Research works printed but not linked: 18

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Metadata

Authors
Wang, S., Yu, D., & Dai, L.
Venue
Journal of the American Chemical Society
Publisher
American Chemical Society (ACS)
Published
2011-03-17
Volume
133
Issue
14
Pages
5182-5185
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
DOI
10.1021/ja1112904
OpenAlex
W2002634552
Cited by
724
References
3
FWCI
28.50
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Polyelectrolyte Functionalized Carbon Nanotubes as Efficient Metal-free Electrocatalysts for Oxygen Reduction. https://app.cochat.ai/papers/10.1021/ja1112904
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Wang, S., Yu, D., & Dai, L. (2011). Polyelectrolyte Functionalized Carbon Nanotubes as Efficient Metal-free Electrocatalysts for Oxygen Reduction. Journal of the American Chemical Society. https://doi.org/10.1021/ja1112904

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.