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Cited by 432

The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.

Catalytic Mechanisms of Sulfur-Doped Graphene as Efficient Oxygen Reduction Reaction Catalysts for Fuel Cells

Zhang, Lipeng, Niu, Jianbing, Li, Mingtao, Xia, Zhenhai·2014·The Journal of Physical Chemistry C
DOI 10.1021/jp410501u
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Abstract

Density functional theory (DFT) was applied to study sulfur-doped graphene clusters as oxygen reduction reaction (ORR) cathode catalysts for fuel cells. Several sulfur-doped graphene clusters with/without Stone–Wales defects were investigated and their electronic structures, reaction free energy, transition states, and energy barriers were calculated to predict their catalytic properties. The results show that sulfur atoms could be adsorbed on the graphene surface, substitute carbon atoms at the graphene edges in the form of sulfur/sulfur oxide, or connect two graphene sheets by forming a sulfur cluster ring. These sulfur-doped graphene clusters with sulfur or sulfur oxide locating at graphene edges show electrocatalytic activity for ORR. Catalytic active sites distribute at the zigzag edge or the neighboring carbon atoms of doped sulfur oxide atoms, which possess large spin or charge density. For those being the active catalytic sites, sulfur atoms with the highest charge density take a two-electron transfer pathway while the carbon atoms with high spin or charge density follow a four-electron transfer pathway. It was predicted from the reaction energy barriers that the sulfur-doped graphene could show ORR catalytic properties comparable to platinum. The prediction is consistent with the experimental results on S-doped graphene.

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Metadata

Authors
Zhang, L., Niu, J., Li, M., & Xia, Z.
Venue
The Journal of Physical Chemistry C
Publisher
American Chemical Society (ACS)
Published
2014-02-07
Volume
118
Issue
7
Pages
3545-3553
ISSN
  • 1932-7447 (ISSN-L)
  • 1932-7455
DOI
10.1021/jp410501u
OpenAlex
W2334028345
Cited by
432
References
45
FWCI
14.63
Type
journal article
Language
en
Open access
closed

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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).

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