Diffusion layer general transport properties

Once again, mass diffusivity J0a, mix and thermal conductivity tc in these expressions represent molecular transport properties via Pick s and Fourier s law, respectively. However, the fluid properties that appear in Sc and St should be interpreted as diffusivities, not molecular transport properties. In terms of the analogies between heat and mass transfer, sometimes 30A,mix represents a diffusivity, and other times it represents a molecular transport property. This ambiguity does not exist in the corresponding expressions for heat transfer. In general, 30a, mix represents a diffusivity in the mass transfer equation and in expressions for the boundary layer thickness Sc. 

Mass transport phenomena usually are effective on distance scales much larger than cell wall and double layer dimensions. Thicknesses of steady-state diffusion layers in mildly stirred systems are in the order of 10 5m. Thus one may generally adopt a picture where the local interphasial properties define the boundary conditions, while the actual mass transfer processes take place on a much larger spatial scale. 

The importance of materials characterization in fuel cell modeling cannot be overemphasized, as model predictions can be only as accurate as their material property input. In general, the material and transport properties for a fuel cell model can be organized in five groups (1) transport properties of electrolytes, (2) electrokinetic data for catalyst layers or electrodes, (3) properties of diffusion layers or substrates, (4) properties of bipolar plates, and (5) thermodynamic and transport properties of chemical reactants and products. 

This chapter is devoted entirely to performance models of conventional catalyst layers (type I electrodes), which rely on reactant supply by gas diffusion. It introduces the general modeling framework and employs it to discuss the basic principles of catalyst layer operation. Structure-based models of CCL rationalize distinct regimes of performance, which are discernible in polarization curves. If provided with basic input data on structure and properties, catalyst layer models reproduce PEFC polarization curves. Consistency between model predictions and experimental data will be evaluated. Beyond polarization curves, performance models provide detailed maps or shapes of reaction rate distributions. In this way, the model-based analysis allows vital conclusions about an optimal design of catalyst layers with maximal catalyst utilization and minimal transport losses to be drawn. 

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