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Fully ceramic anodes such as LSTN-CGO offer some specific advantages compared to conventional cermet anodes. Ceria- and titanate-based phases are both mixed ionic and electronic conductors (MIEC), which leads to very different reaction mechanisms and associated requirements for the microstructure design compared to e.g. Ni-YSZ. Due to the MIEC-property of both solid phases, the transports of neither the electrons nor the oxygen ions are limited to a single phase. As a consequence, composite MIEC electrodes reveal a remarkable property that can be described as ‘composite conductivity’ (for electrons as well as for ions), which is much higher than the (hypothetical) single phase conductivities of the same microstructure. In composite MIEC anodes, the charge carriers can reach the reaction sites even when the volume fraction of one MIEC phase is below the percolation threshold, because the missing contiguity is automatically bridged by the second MIEC phase. The MIEC properties thus open a much larger design space for microstructure optimization of composite electrodes. In this contribution, the composite conductivities of MIEC-based anodes are systematically investigated based on virtual materials testing and stochastic modeling. For this purpose, a large number of 3D microstructures, representing systematic compositional variations of composite anodes, is created by microstructure modeling. The underlying stochastic model is fitted to experimental data from FIB-SEM tomography. For the fitting of the stochastic model, digital twins of the tomography data are created using the methodology of gaussian random fields. By interpolation between and beyond the digital twin compositions, the stochastic model then allows to create numerous virtual 3D microstructures with different compositions, but with realistic properties. The effect of microstructure variation on the composite conductivity is then determined with transport simulations for each 3D microstructure. Furthermore, the corresponding microstructure effects on the cell-performance are determined with a Multiphysics model that describes the anode reaction mechanism. Especially the impact of the composite conductivities on the cell performance is studied in detail. Finally, microstructure design regions are discussed and compared for three different anode materials systems: titanate-CGO (with composite conductivities), Ni-YSZ (with single-phase conductivities), Ni-CGO (with single-phase ionic and composite electronic conductivities).

References: 1. A novel approach for analyzing electrochemical properties of mixed conducting solid oxide fuel cell anode materials by impedance spectroscopy, A. Nenning, A. K. Opitz, T. M. Huber, and J. Fleig, Phys. Chem. Chem. Phys., vol. 16, no. 40, pp. 22321–22336, 2014. 2. Modeling the impedance response of mixed-conducting thin film electrodes, C. Chen, D. Chen, W. C. Chueh, and F. Ciucci, Phys. Chem. Chem. Phys., vol. 16, no. 23, pp. 11573–11583, 2014. Gadolinium doped Ceria (CGO) is a promising material for SOFC anodes because of its mixed ionic electronic conductivity (MIEC), its high catalytic activity for the hydrogen oxida-tion reaction (HOR) and its robustness against degradation. However, many processes in CGO based anodes are still poorly understood and there is no consensus yet on how to inter-pret the corresponding electrochemical impedance spectroscopy (EIS) data. In the literature, especially the low frequency arc is often either depicted as gas impedance or as chemical capacitance process, without conclusive evidence. Moreover, with EIS, charge transport re-sistances in CGO are often not distinguishable from other overlapping processes. For dense thin film MIEC electrodes many sophisticated models are available using transmission line (e.g. [1]) and finite element method (FEM) models (e.g. [2]). In contrast, for porous high per-formance MIEC anodes there are hardly any modelling approaches published, which are ca-pable to capture the complex physico-chemical processes. This is, however, a crucial pre-requisite for a systematic materials optimization. In this contribution we present a model, which enables physical insight into the complex processes involved in a porous CGO based anode on the button cell level. The FEM model is implemented in 1D in the commercial software package Comsol Multiphysics. In this model, the full Nernst-Planck-Poisson equations are implemented for the transport of Ce3+-ions and oxygen ion vacancies. Steady state and linear perturbation simulations are performed in order to compute the DC-behaviour and the EIS-spectra, respectively. The model captures the spa-tial distribution of the reaction zone and associated transport pathways of the charge carriers. Thereby, parameter sets that result in transport limited and surface reaction limited cases are studied. Moreover, the model enables to distinguish the impact of chemical capacitance, HOR resistance and gas impedance on the EIS spectra for button cell conditions. Furthermore, the appropriate material laws, as e.g. the dependency of the HOR re-sistance on the operating conditions (pO2, pH2O), can be deduced from EIS-measurements. By linking bulk material properties, fabrication parameters, microstructure effects and operat-ing conditions with the cell performance, we present a way towards a systematic materials optimization for CGO based 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 model-based approach to link bulk material properties, fabrication parameters, microstructure effects and operating conditions with the cell performance on button cell level. Moreover, the model can be extended to different scales like thin film electrodes, used for fundamental material characterization, as well as to large area cells used for industrial devices with stack architecture. By using a stochastic model for virtual structure variation, also the influence of the microstructure can be assessed in a fully digital way (digital materials design). Hence, with the integration of detailed physicochemical properties over different scales into a single model framework, findings from basic and applied research can be directly used for the industrial development, enabling a systematic optimization of SOFC devices.