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A Review of Graphene‐Based Nanostructural Materials for Both Catalyst Supports and Metal‐Free Catalysts in PEM Fuel Cell Oxygen Reduction Reactions
Author(s) -
Zhou Xuejun,
Qiao Jinli,
Yang Lin,
Zhang Jiujun
Publication year - 2014
Publication title -
advanced energy materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.08
H-Index - 220
eISSN - 1614-6840
pISSN - 1614-6832
DOI - 10.1002/aenm.201301523
Subject(s) - catalysis , materials science , graphene , proton exchange membrane fuel cell , electrolyte , catalyst support , nanotechnology , carbon fibers , chemical engineering , metal , nanomaterials , fuel cells , electrode , composite material , chemistry , composite number , organic chemistry , metallurgy , engineering
A comprehensive overview and description of graphene‐based nanomaterials explored in recent years for catalyst supports and metal‐free catalysts for polymer electrolyte membrane (PEM) fuel cell oxygen reduction reactions (ORR) is presented. The catalyst material structures/morphologies, material selection, and design for synthesis, catalytic performance, catalytic mechanisms, and theoretical approaches for catalyst down‐selection and catalyzed ORR mechanisms are emphasized with respect to the performance of ORR catalysts in terms of both activity and stability. When graphene‐based materials, including graphene and doped graphene, are used as the supporting materials for both Pt/Pt alloy catalysts and non‐precious metal catalyst, the resulting ORR catalysts can give superior catalyst activity and stability compared to those of conventional carbon‐supported catalysts; when they are used as metal‐free ORR catalysts, significant catalytic activity and stability are observed. The nitrogen‐doped graphene materials even show superior performance compared to supported metal catalysts. Challenges including the lack of material mass production, unoptimized catalyst structure/morphology, insufficient fundamental understanding, and testing tools/protocols for performance optimization and validation are identified, and approaches to address these challenges are suggested.