journal article·2001-04-01

Anode Micro Model of Solid Oxide Fuel Cell

S. H. Chan, Z. T. Xia

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Abstract

This paper presents the work on the development of a micro model of a solid oxide fuel cell (SOFC) porous anode, which formed by the mixture of electronic and ionic conductors. The model establishes the complex relationship between the transport phenomena, which includes the transports of electron, ion and gas molecules through the electrode and the electrochemical reaction at the three-phase boundary of the electrode. All forms of polarization losses were considered. Results show that, in general, the smaller the particle size in the anode microstructure, the larger the active area favorable to electrochemical reaction will be and thus lowering the overall polarization. However, the concentration polarization will likely play an important role, in particular for a thick electrode, if the particle size is smaller than certain limit causing substantial increase in flow resistance. The overall polarization reaches a minimum at certain particle size. In addition, it is known that the water vapor content in the hydrogen can greatly influence the polarization but the proper amount of water required for a particular anode design was not well researched, despite its importance. In this study, it was found that very high anode polarization is achieved when pure hydrogen is used. The polarization drops significantly when a small amount of water vapor is added in the hydrogen and the polarization does not change greatly in a wide range of water vapor partial pressure. Finally, there is a strong link between the anode thickness and particle size in anode design. The bigger the particle size in the anode microstructure, the thicker the anode should be for providing sufficient reaction sites. © 2001 The Electrochemical Society. All rights reserved.
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Research context

OpenAlex topics: Advancements in Solid Oxide Fuel Cells · Fuel Cells and Related Materials · Catalysis and Oxidation Reactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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