MODELING PROTON EXCHANGE MEMBRANE FUEL CELL CATHODE CATALYST LAYERS WITH THE LATTICE BOLTZMANN METHOD-DIRECT NUMERICAL SIMULATION FRAMEWORK

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GRUNEWALD-DISSERTATION-2022.pdf (15.35 MB)
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Grunewald, Jon
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School of Chemical and Biomolecular Engineering
School established in 1901 as the School of Chemical Engineering; in 2003, renamed School of Chemical and Biomolecular Engineering
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http://hdl.handle.net/1853/67231
Abstract
One of the main challenges affecting study of the cathode catalyst layer (CCL) in proton exchange membrane fuel cells (PEMFCs) is the lack of detailed understanding of species transport and how it affects electrochemical performance. Researchers have typically used high level approximations that oversimplify the microstructure of the CCL—these are known as macrohomogenous models. However, as the field has progressed, these idealizations have begun to show their flaws, especially in areas of improving catalytic performance with lower Pt-loadings and non-noble metal catalysts. Previously, the microstructure details needed to build an accurate mesoscale model have eluded researchers; however, with advances in tomography and focused-ion-beam scanning-electron-microscopy (FIB-SEM), creating these representations has become possible. Mesoscale modeling in the CCL has been traditionally approached through either the Lattice-Boltzmann-Method (LBM) or electrochemistry coupled Direct-Numerical-Simulation (DNS). These models have been underutilized in the fuel cell community due to their complexity and resource intensiveness; however, with advances in parallel computing, this has become not only a possibility, but a necessity for modeling phenomena such as low Pt loadings and interfacial effects. With these new advances, a synergistic modeling approach can be taken that combines the advantages of each method. Such an approach could shed light on transport and degradation phenomena in PEMFCs, particularly for the catalyst layer and carbon corrosion. For this project, the primary aim was to design and program a coupled LBM-DNS model for a PEMFC electrode based on tomography measurements of the CCL. While there was previously gathered FIB-SEM data, there was no previous Fuller group work on LBM or DNS specifically on PEMFCs. Our collaborators (Dr. Partha Mukherjee and his graduate student Navneet Goswami) have developed a DNS framework for Lithium-ion batteries, but we adapted it to PEMFCs. Due to previous numerical difficulties and the lack of tomography data, this synergistic approach to PEMFCs had not been applied in the literature. Once developed, our second aim was adapting the model to solve issues in the PEMFC that are difficult to model with standard continuum models. One of the issues we looked at was capillary hysteresis, but we also tried to understand the influence of the microstructure on the underlying saturation profile inside of the CCL. Once we developed this framework and looked at these problems, the third aim in this project involved using the LBM-DNS framework to elucidate the mechanism of carbon support corrosion inside of a PEMFC operating at high potential (>0.95 V), one of the most critical issues for PEMFC commercial viability. Previous LBM work on the CCL involves tracking liquid movement through the geometry and little else, whereas previous DNS work doesn’t consider the complex microstructure. However, no work had been done on using computationally intensive packages such as LBM-DNS on modeling corrosion. We used our available electrodes to compare polarization data for not only a variety of different corrosion levels, but also how different operating factors such as the operating temperature and relative humidity influenced the available electrochemically active surface area and performance. Additionally, due to the wide variation in scales, one cannot run the LBM-DNS model in conjunction with standard PEMFC packages. Once we could model the network of equations that describe carbon corrosion, we decided to attempt to look at modelling other phenomena with this framework, such as using a data science approach to model the polarization curve and examining bubble growth in proton exchange membrane electrolyzers. From here, we can see how mesoscale modelling can be extended into the electrochemical community to solve various long-standing problems.
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2022-07-08
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