Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,138

The DOI matches its Crossref record.

Sulfur-Doped Graphene as an Efficient Metal-free Cathode Catalyst for Oxygen Reduction

Yang, Zhi, Yao, Zhen, Li, Guifa, Fang, Guoyong, Nie, Huagui, Liu, Zheng, Zhou, Xuemei, Chen, Xi’an, Huang, Shaoming·2012·ACS Nano

Abstract

Tailoring the electronic arrangement of graphene by doping is a practical strategy for producing significantly improved materials for the oxygen-reduction reaction (ORR) in fuel cells (FCs). Recent studies have proven that the carbon materials doped with the elements, which have the larger (N) or smaller (P, B) electronegative atoms than carbon such as N-doped carbon nanotubes (CNTs), P-doped graphite layers and B-doped CNTs, have also shown pronounced catalytic activity. Herein, we find that the graphenes doped with the elements, which have the similar electronegativity with carbon such as sulfur and selenium, can also exhibit better catalytic activity than the commercial Pt/C in alkaline media, indicating that these doped graphenes hold great potential for a substitute for Pt-based catalysts in FCs. The experimental results are believed to be significant because they not only give further insight into the ORR mechanism of these metal-free doped carbon materials, but also open a way to fabricate other new low-cost NPMCs with high electrocatalytic activity by a simple, economical, and scalable approach for real FC applications.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/nn203393d

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Yang, Z., Yao, Z., Li, G., Fang, G., Nie, H., Liu, Z., Zhou, X., Chen, X., & Huang, S.
Venue
ACS Nano
Published
2011-12-30
Volume
6
Issue
1
Pages
205-211
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2026763931
Cited by
2,138
References
0
FWCI
44.00
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.