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Issue 40, 2017
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Cobalt ion-coordinated self-assembly synthesis of nitrogen-doped ordered mesoporous carbon nanosheets for efficiently catalyzing oxygen reduction

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Abstract

The design and synthesis of a promising porous carbon-based electrocatalyst with an ordered and uninterrupted porous structure for oxygen reduction reaction (ORR) is still a significant challenge. Herein, an efficient catalyst based on cobalt-embedded nitrogen-doped ordered mesoporous carbon nanosheets (Co/N-OMCNS) is successfully prepared through a two-step procedure (cobalt ion-coordinated self-assembly and carbonization process) using 3-aminophenol as a nitrogen source, cobalt acetate as a cobalt source and Pluronic F127 as a mesoporous template. This work indicates that the formation of a two dimensional nanosheet structure is directly related to the extent of the cobalt ion coordination interaction. Moreover, the critical roles of pyrolysis temperature in nitrogen doping and ORR catalytic activity are also investigated. Benefiting from the high surface area and graphitic degree, high contents of graphitic N and pyridinic N, ordered interconnected mesoporous carbon framework, as well as synergetic interaction between the cobalt nanoparticles and protective nitrogen doped graphitic carbon layer, the resultant optimal catalyst Co/N-OMCNS-800 (pyrolyzed at 800 °C) exhibits comparable ORR catalytic activity to Pt/C, superior tolerance to methanol crossover and stability.

Graphical abstract: Cobalt ion-coordinated self-assembly synthesis of nitrogen-doped ordered mesoporous carbon nanosheets for efficiently catalyzing oxygen reduction

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Publication details

The article was received on 17 Jul 2017, accepted on 11 Sep 2017 and first published on 11 Sep 2017


Article type: Paper
DOI: 10.1039/C7NR05208A
Citation: Nanoscale, 2017,9, 15534-15541
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    Cobalt ion-coordinated self-assembly synthesis of nitrogen-doped ordered mesoporous carbon nanosheets for efficiently catalyzing oxygen reduction

    H. Wang, W. Wang, M. Asif, Y. Yu, Z. Wang, J. Wang, H. Liu and J. Xiao, Nanoscale, 2017, 9, 15534
    DOI: 10.1039/C7NR05208A

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