Theoretical analysis of the effect of isotropy on the effective diffusion coefficient in the porous and agglomerated phase of the electrodes of a PEMFC.

In polymer membrane fuel cells (PEMFC), the pore microstructure and the effective diffusion coefficient ( D eff ) of the catalytic layer have a significant impact on the overall performance of the fuel cell. In this work, numerical methods to simulate PEMFC catalytic layers were used to study the effect of isotropy ( I xy ) on the D eff . The proposed methodology studies reconstructed systems by Simulated Annealing imaging with different surface fractions of microstructures composed by two diffusive phases: agglomerates and pores. The D eff is determined numerically by the Finite Volume Method solved for Fick's First Law of Diffusion. The results show that the proposed methodology can effectively quantify the effect of isotropy on the D eff for both diffusion phases. Two trends were obtained in the magnitude of the D eff concerning the change in isotropy: (1) an analytical equation is proposed in this article for D eff ≥ 5 % D 0 and (2) numerical solutions are determined for D eff < 5 % D 0 . In our analytical equation are both a lineal and a logarithmic sweep. When the surface fraction is ∅ = 50%, the D eff decreases more linearly than ∅ = 10 % at the beginning of the isotropy change, which indicates that small changes in isotropy in the particulate material modify it drastically; under these conditions the diffusion coefficient in the pore is predominant. (3) When the surface fraction is less than 50%, the D eff decreases more exponentially at the beginning and more linearly at the end of the isotropy change, which shows that small isotropy changes in the bar-aligned material drastically alter it. In this trend, diffusion in the agglomerate is less affected by isotropy. The proposed methodology can be used as a design tool to improve the mass transport in porous PEMFC electrodes.

Effect of An Image Resolution Change on the Effective Transport Coefficient of Heterogeneous Materials.

Electrochemical electrodes comprise multiple phenomena at different scales. Several works have tried to model such phenomena using statistical techniques. This paper proposes a novel process to work with reduced size images to reconstruct microstructures with the Simulated Annealing method. Later, using the Finite Volume Method, it is verified the effect of the image resolution on the effective transport coefficient (ETC). The method can be applied to synthetic images or images from the Scanning Electron Microscope. The first stage consists of obtaining the image of minimum size, which contains at least 98% of the statistical information of the original image, allowing an equivalent statistical study. The image size reduction was made by applying an iterative decimation over the image using the normalized coarseness to compare the amount of information contained at each step. Representative improvements, especially in processing time, are achieved by reducing the size of the reconstructed microstructures without affecting their statistical behavior. The process ends computing the conduction efficiency from the microstructures. The simulation results, obtained from two kinds of images from different materials, demonstrate the effectivity of the proposed approach. It is important to remark that the controlled decimation allows a reduction of the processor and memory use during the reconstruction and ETC computation of electrodes.