A Particle-Based Model for Effective Properties in Infiltrated Solid Oxide Fuel Cell Electrodes

Abstract

A modeling framework for the numerical reconstruction of the microstructure of infiltrated electrodes is presented in this study. A particle-based sedimentation algorithm is used to generate the backbone, while a novel packing algorithm is used to randomly infiltrate nanoparticles on the surface of backbone particles. The effective properties, such as the connected triple-phase boundary length, the effective conductivity, the effective diffusivity, are evaluated on the reconstructed electrodes by using geometric analysis, finite volume and random-walk methods, and reported in dimensionless form to provide generality to the results. A parametric study on the effect of the main model and operating parameters is performed. Simulations show that the critical loading (i.e., the percolation threshold) increases as the backbone porosity decreases and the nanoparticle diameter increases. Large triple-phase boundary length, specific surface area and good effective conductivity can be reached by infiltration, without detrimental effects on the effective transport properties in gas phase. Simulations reveal a significant sensitivity to the size and contact angle of infiltrated particles, suggesting that the preparation process of infiltrated electrodes should be properly tailored in order to obtain the optimized structures predicted by the model. In the last decade, much attention has been drawn toward nanostructured electrodes for solid oxide fuel cells (SOFCs) prepared via infiltration techniques.1-7 The main reason is reduced polarization resistance, with corresponding increased power density, in comparison with conventional electrodes prepared via traditional mixing and sintering processes. The improved performance of infiltrated electrodes holds even at intermediate temperatures (500-800• C), as demonstrated by a large number of experimental studies. [8][9][10][11][12][13] Other technological advantages are a wide choice of catalyst materials, a good adhesion and a reduced thermal expansion mismatch between the electrode and the electrolyte.3 On the other hand, the long-term stability and the fabrication cost of nanostructured electrodes still need to be properly addressed. 2,3The infiltration (or impregnation) technique involves the deposition of nanoparticles into a pre-sintered backbone of micrometer-size particles.1,3 The backbone is a skeletal structure typically composed of a single component, such as yttria-stabilized zirconia (YSZ) 5,8 or, in alternative, a mixed ionic-electronic conductor (e.g., lanthanum strontium cobalt ferrite LSCF).14 However, composite backbones, such as the usual lanthanum strontium manganite (LSM)/YSZ cathode, have also been used. 1,15 The sintering of the backbone is performed at high temperature in order to ensure structural stability of the electrode and good connection among backbone particles. 3 In the following step, nanoparticles are infiltrated in the backbone using different methods (such as metal salt precipitation, 2 nanoparticle dispersion, 16 molten salts) 1 and then sinte...

Characterization of Degradation in Nickel Impregnated Scandia-Stabilize Zirconia Electrodes during Isothermal Annealing

“…This corresponds to a TPB density of 800 × 10 12 m −2 , which is much greater than the value estimated from the electrochemical model and probably reflects the fact that the model for the infiltrated microstructure is not sufficiently close to reality. Bertei et al 44 present a similar model which predicts a connected TPB density equal to approximately 50 d s 2 , (where d s is the scaffold particle size and is 5 times the infiltrated particle size as in the present experiments) and in the present case corresponds to a connected TPB density of 8 × 10 12 m −2 . This latter value is of a similar order of magnitude to the total TPB density of 18 × 10 12 m −2 measured by tomography in similar electrodes with a doped ceria scaffold infiltrated by nickel 28 and the connected TPB densities estimated in the current specimens before the isothermal annealing ( Figure 16).…”

Optimizing Solid Oxide Fuel Cell Performance to Re-evaluate Its Role in the Mobility Sector

“…For this reason, the optimal ε ae,fl of 0.35 was found to be higher than that for the cermet or infiltrated microstructure (0.27–0.315), due to the influence of the porous medium gas transport. Lastly, for the infiltrated cathode microstructures comprising the CGO backbone coated with LSCF nanoparticles, a backbone-nanoparticle diameter fraction d B / d np = 8 was kept, , and when setting the infiltration loading to maximize λ TPB V an optimal nanoparticle volume fraction of 18% and a porosity ε ae,fl of 27% resulted.…”

Effective Transport Properties

“…The microstructure of the porous media can be obtained from (1) tomography images (García-Salaberri et al 2015a, b, 2018 or can be (2) virtually generated using numerical algorithms (Choi et al 2009;Choi et al 2011;Bertei et al 2014). Volumeaveraged quantities (e.g., composition fraction) and statistical descriptors (e.g., pore size distribution, n-point correlation functions, lineal path function, and chord length function) can be used as objective variables (Pant et al 2014).…”