Towards model-based optimization of CGO/Ni anodes

Gadolinium doped Ceria (CGO) is a promising material for SOFC anodes because of its mixed ionic electronic conductivity, its high catalytic activity for the hydrogen oxidation reaction (HOR) and its robustness against degradation. In SOFC research, electrochemical impedance spectroscopy (EIS) is an essential characterization tool, which serves as a basis for materials optimization on the electrode, cell and stack levels. However, for CGO based electrodes, there is no consensus how to interpret the impedance spectra yet. In the literature, especially the low frequency arc is often either depicted as gas impedance or as chemical capacitance process, without conclusive evidence. Further uncertainties in the interpretation of impedance spectra arise with respect to the operating conditions (especially pO2, pH2O) and to their impact on the HOR resistance. Hence, reliable interpretation of impedance spectra for SOFC with CGO-based anodes requires a detailed model, which captures a) the relevant physico-chemical processes, b) the associated material laws and c) the dependencies on varying operating conditions. In the present contribution, we present an approach for a systematic materials optimization for CGO-based anodes, including EIS measurements, microstructure analysis and finite element modelling with AC and DC mode. The model captures all previously mentioned effects and their impact on the performance of a CGO/Ni-based anode. The computational model is validated and calibrated with EIS-measurements and the impacts of the chemical capacitance and gas impedance on the EIS spectra are illustrated for button cell conditions. The calibrated model is exemplarily used to optimize the CGO/Ni layer thickness. DC results of the extension of the reaction zone are thereby used to understand the different resistive contributions (e.g. from electrochemical conversion, from transport of charge carriers or from gas diffusion) to the total anode impedance. In summary, we present a m