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NUMERICAL MODELING OF THE DISTRIBUTED ELECTROCHEMISTRY AND PERFORMANCE OF SOLID OXIDE FUELS CELLS

机译:固体氧化物燃料电池的电化学及性能的数值模拟

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A cell-level distributed electrochemistry (DEC) modeling tool has been developed to enable predicting trends in solid oxide fuel cell performance by considering the coupled and spatially varying multi-physics that occur within the tri-layer. The approach calculates the distributed electrochemistry within the electrodes, which includes the charge transfer and electric potential fields, ion transport throughout the tri-layer, and gas distributions within the composite and porous electrodes. The thickness of the electrochemically active regions within the electrodes is calculated along with the distributions of charge transfer. The DEC modeling tool can examine the overall SOFC performance based on electrode microstructural parameters, such as particle size, pore size, porosity, electrolyte- and electrode-phase volume fractions, and triple-phase-boundary length. Recent developments in electrode fabrication methods have lead to increased interest in using graded and nano-structured electrodes to improve the electrochemical performance of SOFCs. This paper demonstrates how the DEC modeling tool can be used to help design novel electrode microstructures by optimizing a graded anode for high electrochemical performance.
机译:已开发出一种电池级分布式电化学(DEC)建模工具,以通过考虑在三层内发生的耦合且空间变化的多物理场来预测固体氧化物燃料电池性能的趋势。该方法计算电极内的分布电化学,包括电荷转移和电势场,整个三层中的离子传输以及复合电极和多孔电极内的气体分布。计算电极内电化学活性区域的厚度以及电荷转移的分布。 DEC建模工具可以根据电极微结构参数(例如粒径,孔径,孔隙率,电解质和电极相的体积分数以及三相边界的长度)检查整体SOFC性能。电极制造方法的最新发展已引起人们对使用渐变和纳米结构电极来改善SOFC的电化学性能的兴趣。本文演示了DEC建模工具如何通过优化渐变阳极以实现高电化学性能,从而帮助设计新颖的电极微观结构。

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