3D Microstructure Effects in Ni-YSZ Anodes: Prediction of Effective Transport Properties and Optimization of Redox Stability

Failure Analysis of Ni-8YSZ Electrode under Reoxidation Based on the Real Microstructure

During the operation of solid oxide fuel cells (SOFCs), the Ni-8YSZ anodes are subjected to thermal mismatch and reoxidation, accompanied by the risk of damage and failure. These damages and failures are generally induced by small defects at the microscopic level, leading to the degradation of the structural bearing capacity. Therefore, the distribution and quantification of the stresses in the real microstructure of Ni-8YSZ electrodes is essential. In this study, the real Ni-8YSZ microstructure was reconstructed based on nano-computed tomography, and the stress distribution of the real microstructure was analyzed based on the finite element method under reoxidation and different operating temperatures. The failure probability of 8YSZ at different degrees of reoxidation was evaluated according to the Weibull method, and the amount of damaged 8YSZ elements was statistically counted. The study results indicate a high level of stress in the thin necks and relatively sharp areas of the microstructure. The 8YSZ has a high failure probability at a reoxidation extent of 5-10%.

Modeling the impedance response and steady state behaviour of porous CGO-based MIEC anodes

Mixed ionic and electronic conducting (MIEC) materials recently gained much interest for use as anodes in solid oxide fuel cell (SOFC) applications. However, many processes in MIEC-based porous anodes are still poorly understood and the appropriate interpretation of corresponding electrochemical impedance spectroscopy (EIS) data is challenging. Therefore, a model which is capable to capture all relevant physico-chemical processes is a crucial prerequisite for systematic materials optimization. In this contribution we present a comprehensive model for MIEC-based anodes providing both the DC-behaviour and the EIS-spectra. The model enables one to distinguish between the impact of the chemical capacitance, the reaction resistance, the gas impedance and the charge transport resistance on the EIS-spectrum and therewith allows its appropriate interpretation for button cell conditions. Typical MIEC-features are studied with the model applied to gadolinium doped ceria (CGO) anodes with different microstructures. The results obtained for CGO anodes reveal the spatial distribution of the reaction zone and associated transport distances for the charge carriers and gas species. Moreover, parameter spaces for transport limited and surface reaction limited situations are depicted. By linking bulk material properties, microstructure effects and the cell design with the cell performance, we present a way towards a systematic materials optimization for MIEC-based anodes.

Predicting permeability via statistical learning on higher-order microstructural information

Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the geometry of the pore microstructure facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we study the predictability of different structural descriptors via both linear regressions and neural networks. A large data set of 30,000 virtual, porous microstructures of different types, including both granular and continuous solid phases, is created for this end. We compute permeabilities of these structures using the lattice Boltzmann method, and characterize the pore space geometry using one-point correlation functions (porosity, specific surface), two-point surface-surface, surface-void, and void-void correlation functions, as well as the geodesic tortuosity as an implicit descriptor. Then, we study the prediction of the permeability using different combinations of these descriptors. We obtain significant improvements of performance when compared to a Kozeny-Carman regression with only lowest-order descriptors (porosity and specific surface). We find that combining all three two-point correlation functions and tortuosity provides the best prediction of permeability, with the void-void correlation function being the most informative individual descriptor. Moreover, the combination of porosity, specific surface, and geodesic tortuosity provides very good predictive performance. This shows that higher-order correlation functions are extremely useful for forming a general model for predicting physical properties of complex materials. Additionally, our results suggest that artificial neural networks are superior to the more conventional regression methods for establishing quantitative structure-property relationships. We make the data and code used publicly available to facilitate further development of permeability prediction methods.

An Anisotropic Microstructure Evolution in a Solid Oxide Fuel Cell Anode

The presented research shows that the long-term operation of a solid oxide fuel cell can lead to substantial anisotropic changes in anode material. The morphology of microstructure in the investigated stack was observed before and after the aging test using electron nanotomography. The microstructural parameters were estimated based on the obtained digital representation of the anode microstructure. Anisotropy was discovered in two of the three phases that constitute the anode, namely nickel and pores. The third component of the anode, which is yttrium-stabilized zirconia, remains isotropic. The changes appear at the microscale and significantly affect the transport phenomena of electrons and gasses. The obtained results indicate that the reference anode material that represents the microstructure before the aging test has isotropic properties which evolve toward strong anisotropy after 3800 h of constant operation. The presented findings are crucial for a credible numerical simulation of solid oxide fuel cells. They indicate that all homogeneous models must adequately account for the microstructure parameters that define the anisotropy of transport phenomena, especially if microstructural data is taken from a post-operational anode.

Microstructure degradation of Ni/CGO anodes for solid oxide fuel cells after long operation time using 3D reconstructions by FIB tomography

The 3D reconstructions of SOFC anode microstructure aged up to 20 000 h under realistic conditions was carried out with FIB/SEM tomography in order to calculate the microstructure key parameters.

Solid oxide fuel cell interconnect design optimization considering the thermal stresses

The mechanical failure of solid oxide fuel cell (SOFC) components may cause cracks with consequences such as gas leakage, structure instability and reduction of cell lifetime. A comprehensive 3D model of the thermal stresses of an anode-supported planar SOFC is presented in this work. The main objective of this paper is to get an interconnect optimized design by evaluating the thermal stresses of an anode-supported SOFC for different designs, which would be a new criterion for interconnect design. The model incorporates the momentum, mass, heat, ion and electron transport, as well as steady-state mechanics. Heat from methane steam reforming and water–gas shift reaction were considered in our model. The results examine the relationship between the interconnect structures and thermal stresses in SOFC at certain mechanical properties. A wider interconnect of the anode side lowers the stress obviously. The simulation results also indicate that thermal stress of coflow design is smaller than that of counterflow, corresponding to the temperature distribution. This study shows that it is possible to design interconnects for an optimum thermal stress performance of the cell.

3D Microstructure Effects in Ni-YSZ Anodes: Influence of TPB Lengths on the Electrochemical Performance

3D microstructure-performance relationships in Ni-YSZ anodes for electrolyte-supported cells are investigated in terms of the correlation between the triple phase boundary (TPB) length and polarization resistance (R_pol). Three different Ni-YSZ anodes of varying microstructure are subjected to eight reduction-oxidation (redox) cycles at 950 °C. In general the TPB lengths correlate with anode performance. However, the quantitative results also show that there is no simplistic relationship between TPB and R_pol. The degradation mechanism strongly depends on the initial microstructure. Finer microstructures exhibit lower degradation rates of TPB and R_pol. In fine microstructures, TPB loss is found to be due to Ni coarsening, while in coarse microstructures reduction of active TPB results mainly from loss of YSZ percolation. The latter is attributed to weak bottlenecks associated with lower sintering activity of the coarse YSZ. The coarse anode suffers from complete loss of YSZ connectivity and associated drop of TPB_active by 93%. Surprisingly, this severe microstructure degradation did not lead to electrochemical failure. Mechanistic scenarios are discussed for different anode microstructures. These scenarios are based on a model for coupled charge transfer and transport, which allows using TPB and effective properties as input. The mechanistic scenarios describe the microstructure influence on current distributions, which explains the observed complex relationship between TPB lengths and anode performances. The observed loss of YSZ percolation in the coarse anode is not detrimental because the electrochemical activity is concentrated in a narrow active layer. The anode performance can be predicted reliably if the volume-averaged properties (TPB_active, effective ionic conductivity) are corrected for the so-called short-range effect, which is particularly important in cases with a narrow active layer.