X-Ray Computed Tomography Visualization of Electrode Morphology Changes during Start-up/Shut-Down Cycling in Polymer Electrolyte Fuel Cells
Bibliographic record
Abstract
Optimization of polymer electrolyte fuel cells can be achieved with detailed characterization of the operational behavior of the catalyst layer (CL). Moreover, understanding its operational degradation due to the changes to its multi-scale, composite structure is important for durability improvements and retaining high fuel cell performance over time. Start-up/shut-down (SU/SD) cycles are known to induce temporarily high, oxidizing potentials at the cathode electrode due to a propagating hydrogen-air front along the anode active area. These high potentials cause carbon corrosion and catalyst layer degradation [1], which can be observed during the lifetime of a test cell using advanced imaging techniques. Scanning electron microscopy (SEM) has typically been used to characterize the CL structure since it provides high contrast and high-resolution imaging [2]. However, SEM requires considerable sample handling, sample is destroyed during preparation, is limited to 2D visualization, and can suffer from edge effects, which makes segmentation and interpretation of CL lifetime degradation studies difficult. In contrast, the use of X-ray computed tomography (XCT) allows 3D and 4D non-intrusive imaging. This virtual dataset allows visualization of internal fuel cell components, such as the CL, over the test lifetime. To date, XCT studies on CL degradation have investigated changes instigated by voltage cycling accelerated stress testing; as well as in-operando imaging to obtain water distribution [3,4]. The objective of the present work is to assess temporal and local morphological electrode degradation effects caused by SU/SD cycling via 4D identical-location micro-XCT imaging with a custom, small scale fuel cell fixture. The results are compared against the equivalent case for voltage cycling in order to elucidate any differences in the specific degradation phenomena. In addition, impacts of gas flow distribution and anode/cathode channel alignment on local degradation is being investigated. Physical changes in the cathode-CL were periodically measured from beginning of life (BOL) to end of life (EOL), as shown in Figure 1, and correlated to the corrosion of the carbon support structure and platinum dissolution. The resultant data indicates a gradual degradation of the cathode-CL. Furthermore, the subsequent morphological changes were in good agreement with the losses in fuel cell performance and the deterioration of the electrochemical surface area. A similar degradation trend was observed in the voltage-cycling degradation study reported previously by our team [3]. However, a variance in the degradation of landing versus channel regions between these two studies exists. Where in this work more degradation was observed under the channel region, whereas, more degradation in the channel was observed in the voltage-cycling study. This contrast can be resolved when one considers that the cell voltage in the voltage-cycling study was applied uniformly under constant gas flow, while the degradation from the SU/SD cycling is influenced by the movement of the reacting gases along the anode active area. At BOL, the studied cathode-CL featured local variations in thickness with mud-cracks randomly distributed across the active area. Upon SU/SD cycling, the most corrosion of the carbon support structure and platinum dissolution was observed at thin cathode-CL regions along pre-existing crack formations. In addition, the gas flow distribution impacts with reduced channel reactant flow and reduced anode/cathode landing alignment were investigated. It was found that an overall increased cathode-CL degradation by SU/SD cycling occurred in the flow channel with reduced reactant flow, while misalignment of the anode/cathode landing did not influence the CCL degradation, compared to the regular aligned cells. Overall, the in situ electrochemical diagnostics and micro-XCT results showed direct relationships between carbon corrosion, platinum dissolution and electrode capacitance loss from SU/SD cycling. These morphological observations are thus believed to be responsible for much of the performance degradation during SU/SD cycling. Acknowledgements This research was supported by Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, Automotive Partnership Canada, Ballard Power Systems, Canada Research Chairs, Western Economic Diversification Canada, and Simon Fraser University References 1. Macauley, et al., J. Electrochem. Soc. 2018;165(6):F3148–60. Tavassoli, et al., J. Power Sources 2016;322:17–25. White, et al., J. Power Sources 2017;350:94–102. White, et al., Sci. Rep. 2019;9(1):1–12. Figure 1
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".