Abstract

Designing optimal microstructures for solid oxide fuel cell (SOFC) electrodes is complicated due to the multitude of electro-chemo-physical phenomena taking place simultaneously that directly affect working conditions of a SOFC electrode and its performance. In this study, a new design paradigm is presented to obtain a balance between electrochemical sites in the form of triple phase boundary (TPB) density and physical properties in the form of gas diffusivity in the microstructure of a SOFC electrode. The method builds on top of a previously developed methodology for digital realization of generic microstructures with different geometric properties in ionic or electronic conductor grains. The obtained realizations of SOFC electrode are then used to calculate TPB density and gas transport factor. In the next step, based on the obtained database, a neural network is trained to relate input geometrical parameters to those output properties. The results indicate that the TPB density is less sensitive to the geometry than the gas transport factor. Also, the smaller particles in the ionic and electronic conductor phase lead to a higher amount of TPB density. The presented methodology is also used to obtain the maximum feasible properties of microstructures and their related geometric characteristics for special target functions like maximum reaction sites and gas diffusivity in a realized model. The tradeoff between input and output parameters is another application of this modeling approach which demonstrates the TPB density and gas transport factor variation versus the geometric anisotropy of particles and porosity, respectively.

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