Solid oxide fuel cell microstructure and performance modeling

The fundamental operation of Solid Oxide Fuel Cells (SOFCs) relies on the liberation of electrons at reaction sites within porous electrodes. These reaction sites, or triple-phase boundary (TPB) points, must be percolated to allow for reactants and products to flow to and from these sites. Due to the fact that electrochemical reactions in composite electrodes are dependent on the presence of TPB sites, a direct link exists between SOFC electrode microstructures and electrochemical performance. Recently, the development of advanced tomography and imaging techniques has allowed for this link to be better understood and quantified. This thesis presents the development of a novel effective conductivity model (ResNet) for 3D composite, anisotropic microstructures in the context of Ni-YSZ electrode characterization. The ResNet model is first used to derive the effective conductivity of simple structures, conductivities of which can be found in the literature. Good agreement was found in this initial study. The model is then used to compute the effective conductivities of more complex synthetic microstructures, comparing model outputs to those given by COMSOL Multiphysics, a commercial modeling platform. It was found that for a sufficiently high resolution, both models converge to the same results. Varying the discretization resolution allowed for an optimum discretization resolution to be determined, based on the mean particle size used for fabrication. The introduction of Volume Elements into the ResNet model is then presented, and the optimum aggregation resolution is extracted from a set of simulations. This allowed for the analysis of a real SOFC anode microstructure to be carried out, and underlined the importance of selecting a microstructure sample of a size that can be considered representative of the entire electrode. After a series of simulations on synthetically generated microstructures, several microstructural parameters are varied to carry out a sensitivity analysis on the effective conductivities and current densities of the microstructures. This analysis yielded an optimum ratio of 7 particles per structure length for microstructure size representativeness. Using the parameters derived from the studies presented in this thesis, the effective conductivities of two experimental Ni/10ScSZ anodes are extracted using the ResNet model and compared to their experimentally determined values. Excellent agreement was obtained, validating the ResNet model and associated work. In a final instance, it was shown that using the ResNet model in the electronic phase in conjunction with the VOF model developed by Golbert et al. does not yield a noticeable difference in current density output when compared to results obtained without using the ResNet. When applied to the ionic phase however, using the ResNet model in conjunction with the VOF model is found to predict as much as 50% lower computed area current densities than when the volume fraction average model is used.Open Acces

Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes - Validation against experimental measurements and prediction of electrochemical performance

© 2015 Elsevier Ltd. All rights reserved.The effective conductivity of thick-film solid oxide fuel cell (SOFC) electrodes plays a key role in their performance. It determines the ability of the electrode to transport charge to/from reaction sites to the current collector and electrolyte. In this paper, the validity of the recently proposed 3D resistor network model for the prediction of effective conductivity, the ResNet model, is investigated by comparison to experimental data. The 3D microstructures of Ni/10ScSZ anodes are reconstructed using tomography through the focused ion beam and scanning electron microscopy (FIB-SEM) technique. This is used as geometric input to the ResNet model to predict the effective conductivities, which are then compared against the experimentally measured values on the same electrodes. Good agreement is observed, supporting the validity of the ResNet model for predicting the effective conductivity of SOFC electrodes. The ResNet model is then combined with the volume-of-fluid (VOF) method to integrate the description of the local conductivity (electronic and ionic) in the prediction of electrochemical performance. The results show that the electrochemical performance is in particular sensitive to the ionic conductivity of the electrode microstructure, highlighting the importance of an accurate description of the local ionic conductivity

Solid Oxide Fuel Cell Electrode 3D Microstructure and Performance Modeling

A strong correlation exists between the performance of Solid Oxide Fuel Cells (SOFCs) and their electrode microstructures, requiring an improved understanding of this relationship if more effective application-specific SOFC electrodes are to be designed. A model has been developed capable of generating a random 3D electrode microstructure and predicting its performance by analyzing structure properties such as porosity, percolation of the various phases and the length and distribution of triple phase boundaries. A Monte Carlo process is used initially to randomly position spherical particles of the three different phases, in a packed bed. Next, the pore former particles are removed. The remaining particles are then expanded uniformly to represent the sintering process, resulting in a network of particles of ionic and electronic phases overlapping each other, creating a distinctive, examinable electrode. This paper presents the impact of a range of technologically important parameters such as particle size and sintering expansion coefficient on electrode performance

Solid Oxide Fuel Cell Electrode 3D Microstructure and Performance Modeling

A strong correlation exists between the performance of Solid Oxide Fuel Cells (SOFCs) and their electrode microstructures, requiring an improved understanding of this relationship if more effective application-specific SOFC electrodes are to be designed. A model has been developed capable of generating a random 3D electrode microstructure and predicting its performance by analyzing structure properties such as porosity, percolation of the various phases and the length and distribution of triple phase boundaries. A Monte Carlo process is used initially to randomly position spherical particles of the three different phases, in a packed bed. Next, the pore former particles are removed. The remaining particles are then expanded uniformly to represent the sintering process, resulting in a network of particles of ionic and electronic phases overlapping each other, creating a distinctive, examinable electrode. This paper presents the impact of a range of technologically important parameters such as particle size and sintering expansion coefficient on electrode performance

Towards the 3D modeling of the effective conductivity of solid oxide fuel cellelectrodes – II. Computationalparameters

The effective conductivity of a thick-film solid oxide fuel cell (SOFC) electrode is an important characteristic used to link the microstructure of the electrode to its performance. A 3D resistor network model, the ResNet model, developed to determine the effective conductivity of a given SOFC electrode microstructure was introduced in earlier work (Rhazaoui et al., Chem. Eng. Sci. 99, 161-170, 2013). The approach is based on the discretization of each structure into voxels (small cubic elements discretizing the microstructure). In this paper, synthetic structures of increasing complexity are analyzed before an optimum discretization resolution per particle diameter is determined. The notion of Volume Elements (VEs), based on the Volume-Of-Fluid method, is then introduced in the model to allow larger structures to be modelled and is used to analyze synthetic structures as well as an experimental Ni/10ScSZ electrode. The behaviour of the model output is examined with respect to increasing aggregation resolutions for several synthetic microstructures of varying compositions, with the aid of extracted skeletonized paths of charge-conducting pathways. A ratio of VE size to voxel size of 5 is shown to be appropriate. The first comparison of calculated and measured effective conductivities is presented for the Ni/10ScSZ electrode considered. The computed effective conductivities are found to be consistent with observations made on the microstructure itself and skeletonized network paths, and support the findings of earlier work with respect to the minimum sample size required to characterize the entire anode from which it is extracted

Towards the 3D modeling of the effective conductivity of solid oxide fuel cell electrodes: I. Model development

The effective conductivity of a thick-film solid oxide fuel cell (SOFC) electrode is an important characteristic used to link the microstructure of the electrode to its performance. A 3D resistor network model that has been developed to determine the effective conductivity of a given SOFC electrode microstructure, the Resistor Network or ResNet model, is introduced in this paper. The model requires the discretization of a 3D microstructure into voxels, based on which a mixed resistor network is drawn. A potential difference is then applied to this network and yields the corresponding currents, allowing the equivalent resistance and hence conductivity of the entire structure to be determined. An overview of the ResNet modeling methodology is presented. The approach is general and can be applied to structures of arbitrary complexity, for which appropriate discretization resolutions are required. The validity of the model is tested by applying it to a set of model structures and comparing calculated effective conductivity values against analytical results. © 2013 Elsevier Ltd

Towards the 3D modeling of the effective conductivity of solid oxide fuel cellelectrodes – II. Computationalparameters

The effective conductivity of a thick-film solid oxide fuel cell (SOFC) electrode is an important characteristic used to link the microstructure of the electrode to its performance. A 3D resistor network model, the ResNet model, developed to determine the effective conductivity of a given SOFC electrode microstructure was introduced in earlier work (Rhazaoui et al., Chem. Eng. Sci. 99, 161-170, 2013). The approach is based on the discretization of each structure into voxels (small cubic elements discretizing the microstructure). In this paper, synthetic structures of increasing complexity are analyzed before an optimum discretization resolution per particle diameter is determined. The notion of Volume Elements (VEs), based on the Volume-Of-Fluid method, is then introduced in the model to allow larger structures to be modelled and is used to analyze synthetic structures as well as an experimental Ni/10ScSZ electrode. The behaviour of the model output is examined with respect to increasing aggregation resolutions for several synthetic microstructures of varying compositions, with the aid of extracted skeletonized paths of charge-conducting pathways. A ratio of VE size to voxel size of 5 is shown to be appropriate. The first comparison of calculated and measured effective conductivities is presented for the Ni/10ScSZ electrode considered. The computed effective conductivities are found to be consistent with observations made on the microstructure itself and skeletonized network paths, and support the findings of earlier work with respect to the minimum sample size required to characterize the entire anode from which it is extracted

Towards the 3D modelling of the effective conductivity of solid oxide fuel cell electrodes - Validation against experimental measurements and prediction of electrochemical performance

© 2015 Elsevier Ltd. All rights reserved.The effective conductivity of thick-film solid oxide fuel cell (SOFC) electrodes plays a key role in their performance. It determines the ability of the electrode to transport charge to/from reaction sites to the current collector and electrolyte. In this paper, the validity of the recently proposed 3D resistor network model for the prediction of effective conductivity, the ResNet model, is investigated by comparison to experimental data. The 3D microstructures of Ni/10ScSZ anodes are reconstructed using tomography through the focused ion beam and scanning electron microscopy (FIB-SEM) technique. This is used as geometric input to the ResNet model to predict the effective conductivities, which are then compared against the experimentally measured values on the same electrodes. Good agreement is observed, supporting the validity of the ResNet model for predicting the effective conductivity of SOFC electrodes. The ResNet model is then combined with the volume-of-fluid (VOF) method to integrate the description of the local conductivity (electronic and ionic) in the prediction of electrochemical performance. The results show that the electrochemical performance is in particular sensitive to the ionic conductivity of the electrode microstructure, highlighting the importance of an accurate description of the local ionic conductivity