Effect of Cobalt Loading in Nitrogen-Doped Carbon on Oxygen Reduction Reaction for PEM Fuel Cells

2012 ◽  
Vol 557-559 ◽  
pp. 1218-1222 ◽  
Author(s):  
Sheng Zhou Chen ◽  
Wei Yang ◽  
Liang Wei Li ◽  
Han Bo Zou ◽  
Wei Ming Lin
Keyword(s):  
Oxygen Reduction Reaction ◽  
Oxygen Reduction ◽  
Condensation Reaction ◽  
Rotating Disk ◽  
Pem Fuel Cells ◽  
Reduction Reaction ◽  
Rotating Disk Electrode ◽  
Formaldehyde Resin ◽  
Nitrogen Doped ◽  
Nitrogen Doped Carbon

Nitrogen-doped carbon supported Co catalysts (CoNC) were synthesized via condensation reaction of pre-polymer of melamine formaldehyde resin with addition of cobalt nitrate salt, followed by carbonization in nitrogen. Rotating disk electrode technique (RDE) and scanning electron microscopy (SEM) with energy dispersive X-ray spectrometry (EDS) were used to identify the structure and oxygen reduction reaction (ORR) kinetics of the catalysts. The results show that the catalysts with 3.77 wt% Co loading yield the best ORR catalytic activity. Koutecky-Levich plots indicate ORR mechanism is governed by mixed mechanisms and the measured electron number varies between 2 and 4. SEM image shows an irregular lamellar structure of CoNC catalyst formed at high temperature, and different Co loadings in CoNC catalyst do not change its surface morphology.

scholarly journals N8− Polynitrogen Stabilized on Nitrogen-Doped Carbon Nanotubes as an Efficient Electrocatalyst for Oxygen Reduction Reaction

Catalysts ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 864 ◽  
Author(s):  
Zhenhua Yao ◽  
Ruiyang Fan ◽  
Wangyang Ji ◽  
Tingxuan Yan ◽  
Maocong Hu
Keyword(s):  
Carbon Nanotubes ◽  
Oxygen Reduction Reaction ◽  
Oxygen Reduction ◽  
Rotating Disk ◽  
Reduction Reaction ◽  
Rotating Disk Electrode ◽  
Nitrogen Doped ◽  
Metal Free ◽  
Temperature Programmed ◽  
Nitrogen Doped Carbon

In this work, non-traditional metal-free polynitrogen chain N8− deposited on a nitrogen-doped carbon nanotubes (PN-NCNT) catalyst was successfully synthesized by a facile cyclic voltammetry (CV) approach, which was further tested in an oxygen reduction reaction (ORR). The formation of PN on NCNT was confirmed by attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR) and Raman spectroscopy. Partial positive charge of carbon within NCNT facilitated electron transfer and accordingly induced the formation of more PN species compared to CNT substrate as determined by temperature-programmed decomposition (TPD). Rotating disk electrode (RDE) measurements suggested that a higher current density was achieved over PN-NCNT than that on PN-CNT catalyst, which can be attributed to formation of the larger amount of N8− on NCNT. Kinetic study suggested a four-electron pathway mechanism over PN-NCNT. Moreover, it showed long stability and good methanol tolerance, which indicates its great potential application. This work provides insights on designing and synthesizing non-traditional metal-free catalysts for ORR in fuel cells.

scholarly journals Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3858
Author(s):  
Monica Dan ◽  
Adriana Vulcu ◽  
Sebastian A. Porav ◽  
Cristian Leostean ◽  
Gheorghe Borodi ◽  
...  
Keyword(s):  
Oxygen Reduction Reaction ◽  
Oxygen Reduction ◽  
Rotating Disk ◽  
Reduction Reaction ◽  
Machine Learning Algorithms ◽  
Rotating Disk Electrode ◽  
X Ray ◽  
Synthesis Conditions ◽  
Characterization Techniques ◽  
Doped Graphene

Four N-doped graphene materials with a nitrogen content ranging from 8.34 to 13.1 wt.% are prepared by the ball milling method. This method represents an eco-friendly mechanochemical process that can be easily adapted for industrial-scale productivity and allows both the exfoliation of graphite and the synthesis of large quantities of functionalized graphene. These materials are characterized by transmission and scanning electron microscopy, thermogravimetry measurements, X-ray powder diffraction, X-ray photoelectron and Raman spectroscopy, and then, are tested towards the oxygen reduction reaction by cyclic voltammetry and rotating disk electrode methods. Their responses towards ORR are analysed in correlation with their properties and use for the best ORR catalyst identification. However, even though the mechanochemical procedure and the characterization techniques are clean and green methods (i.e., water is the only solvent used for these syntheses and investigations), they are time consuming and, generally, a low number of materials can be prepared, characterized and tested. In order to eliminate some of these limitations, the use of regression learner and reverse engineering methods are proposed for facilitating the optimization of the synthesis conditions and the materials’ design. Thus, the machine learning algorithms are applied to data containing the synthesis parameters, the results obtained from different characterization techniques and the materials response towards ORR to quickly provide predictions that allow the best synthesis conditions or the best electrocatalysts’ identification.

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