A Three-Dimensional Numerical Assessment of Heterogeneity Impact on a Solid Oxide Fuel Cell’s Anode Performance

Prokop, Tomasz A.; Berent, Katarzyna; Szmyd, Janusz S.; Brus, Grzegorz

doi:10.3390/catal8110503

Cited by 19 publications

(10 citation statements)

References 26 publications

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“…The phase interface area in the case of the cathode was computed using the marching cube method. For details regarding microstructure quantification, see our previous articles [27,28].…”

Section: Microstructure Quantificationmentioning

confidence: 99%

A Three-Dimensional Microstructure-Scale Simulation of a Solid Oxide Fuel Cell Anode—The Analysis of Stack Performance Enhancement After a Long-Term Operation

et al. 2019

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In this research, we investigate the connection between an observed enhancement in solid oxide fuel cell stack performance and the evolution of the microstructure of its electrodes. A three dimensional, numerical model is applied to predict the porous ceramic-metal electrode performance on the basis of microstructure morphology. The model features a non-continuous computational domain based on the digital reconstruction obtained using focused ion beam scanning electron microscopy (FIB-SEM) electron nanotomography. The Butler–Volmer equation is used to compute the charge transfer at reaction sites, which are modeled as distinct locally distributed features of the microstructure. Specific material properties are accounted for using interpolated experimental data from the open literature. Mass transport is modeled using the extended Stefan–Maxwell model, which accounts for both the binary, and the Knudsen diffusion phenomena. The simulations are in good agreement with the experimental data, correctly predicting a decrease in total losses for the observed microstructure evolution. The research supports the hypothesis that the performance enhancement was caused by a systematic change in microstructure morphology.

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“…The phase interface area in the case of the cathode was computed using the marching cube method. For details regarding microstructure quantification, see our previous articles [27,28].…”

Section: Microstructure Quantificationmentioning

confidence: 99%

A Three-Dimensional Microstructure-Scale Simulation of a Solid Oxide Fuel Cell Anode—The Analysis of Stack Performance Enhancement After a Long-Term Operation

et al. 2019

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“…Their findings demonstrated that MOOSE framework [23] yields a notable improvement in the efficiency of highperformance computing applied to microstructures in SOFC. Despite the large number of research that has been done on microscale physical modeling of SOFC [20,21,22,23,24,25,26,27], mostly are focused on conventional microstructure designs whose 3D reconstructions are acquired with tomography methods (FIB-SEM in particular). The potential of more ordered microstructure configurations, distinct from conventional structures typically produced through tape casting [28], powder ball milling [29], or screen printing [30], remains largely unexplored in this context.…”

Section: Introductionmentioning

confidence: 99%

Significance of advanced porous configurations in enhancing solid oxide fuel cell performance: a comparative analysis between conventional porous anodes and state-of-the-art variants

Abbasi,

Babaei,

Rabbani

et al. 2024

Preprint

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Three different configurations of the porous anode of solid oxide fuel cell (SOFC) have been computationally synthesized and analyzed with respect to their electrochemical performance and topological properties. In addition to the conventional Ni/YSZ configuration of SOFC, which is usually fabricated using screen-printing, two novel designs (fibrous and lattice microstructures) are synthesized and tested. For each class of configurations, a numerical framework has been developed that can generate microstructures with specified topological characteristics. Finite volume method is employed to investigate transport phenomena and electrochemical reactions occurring within the active layer of porous anode cermet. Utilization of synthetically generated microstructures enables the direct study of certain microstructural and image acquisition attributes that may be inherently fixed within the confines and limits of a destructive 3D imaging. For instance, results showed how the choice of voxel size can greatly alter the measured Triple Phase Boundary (TPB) and the electrochemical performance. The investigation further demonstrated that lattice and fibrous structures produce an increased current density of 4.8 and 1.4 times, respectively, compared to the established conventional configuration. Finally, gradient microstructures have demonstrated the capacity to enhance electrochemical performance when subjected to careful fabrication methodologies.

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“…Thus, the SOFC electrode is characterized by high internal complexity. In this respect, the electrode's ability to effectively transport the species to and from the reaction site, described by its microstructure's morphological parameters, is of great significance for the cell's overall performance [4,5]. Elaboration of those parameters, like porosity, connectivity, or triple-phase boundary density (reaction domain), becomes a crucial part of any SOFC analysis [6,7].…”

Section: Introductionmentioning

confidence: 99%

Swarm Intelligence-Based Methodology for Scanning Electron Microscope Image Segmentation of Solid Oxide Fuel Cell Anode

et al. 2021

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Segmentation of images from scanning electron microscope, especially multiphase, poses a drawback in their microstructure quantification process. The labeling process must be automatized due to the time consumption and irreproducibility of the manual labeling procedure. Here we show a swarm intelligence-driven filtration methodology performed on raw solid oxide fuel cell anode’s material images to improve the segmentation methods’ performance. The methodology focused on two significant parts of the segmentation process, which are filtering and labeling. During the first one, the images underwent filtering by applying a series of filters, whose operation parameters were determined using Particle Swarm Optimization upon a dedicated cost function. Next, Seeded Region Growing, k-Means Clustering, Multithresholding, and Simple Linear Iterative Clustering Superpixel algorithms were utilized to label the filtered images’ regions into consecutive phases in the microstructure. The improvement was presented for three different metrics: the Misclassification Ratio, Structural Similarity Index Measure, and Mean Squared Error. The obtained distribution of metrics’ performances was based on 200 images, with and without filtering. Results indicate an improvement up to 29%, depending on the metric and method used. The presented work contributes to the ongoing efforts to automatize segmentation processes fully for an increasing number of tomographic measurements, particularly in solid oxide fuel cell research.

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A Three-Dimensional Numerical Assessment of Heterogeneity Impact on a Solid Oxide Fuel Cell’s Anode Performance

Cited by 19 publications

References 26 publications

A Three-Dimensional Microstructure-Scale Simulation of a Solid Oxide Fuel Cell Anode—The Analysis of Stack Performance Enhancement After a Long-Term Operation

A Three-Dimensional Microstructure-Scale Simulation of a Solid Oxide Fuel Cell Anode—The Analysis of Stack Performance Enhancement After a Long-Term Operation

Significance of advanced porous configurations in enhancing solid oxide fuel cell performance: a comparative analysis between conventional porous anodes and state-of-the-art variants

Swarm Intelligence-Based Methodology for Scanning Electron Microscope Image Segmentation of Solid Oxide Fuel Cell Anode

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