Effect of microstructure of nitrogen-doped graphene on oxygen reduction activity in fuel cells

The development of fuel cells as clean-energy technologies is largely limited by the prohibitive cost of the noble-metal catalysts needed for catalyzing the oxygen reduction reaction (ORR) in fuel cells. A fundamental understanding of catalyst design principle that links material structures to the c...

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Veröffentlicht in:Langmuir : the ACS journal of surfaces and colloids. - 1992. - 28(2012), 19 vom: 15. Mai, Seite 7542-50
1. Verfasser: Zhang, Lipeng (VerfasserIn)
Weitere Verfasser: Niu, Jianbing, Dai, Liming, Xia, Zhenhai
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2012
Zugriff auf das übergeordnete Werk:Langmuir : the ACS journal of surfaces and colloids
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:The development of fuel cells as clean-energy technologies is largely limited by the prohibitive cost of the noble-metal catalysts needed for catalyzing the oxygen reduction reaction (ORR) in fuel cells. A fundamental understanding of catalyst design principle that links material structures to the catalytic activity can accelerate the search for highly active and abundant nonmetal catalysts to replace platinum. Here, we present a first-principles study of ORR on nitrogen-doped graphene in acidic environment. We demonstrate that the ORR activity primarily correlates to charge and spin densities of the graphene. The nitrogen doping and defects introduce high positive spin and/or charge densities that facilitate the ORR on graphene surface. The identified active sites are closely related to doping cluster size and dopant-defect interactions. Generally speaking, a large doping cluster size (number of N atoms >2) reduces the number of catalytic active sites per N atom. In combination with N clustering, Stone-Wales defects can strongly promote ORR. For four-electron transfer, the effective reversible potential ranges from 1.04 to 1.15 V/SHE, depending on the defects and cluster size. The catalytic properties of graphene could be optimized by introducing small N clusters in combination with material defects
Beschreibung:Date Completed 07.09.2012
Date Revised 15.05.2012
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1520-5827
DOI:10.1021/la2043262