Interactions between Catalyst Layer Degradation and Liquid Water Distribution in Polymer Electrolyte Fuel Cells
Bibliographic record
Abstract
Managing liquid water distribution in PEFCs is critical to desirable high power density operation and cell durability [1–3]. Degradation modes such as carbon corrosion in the cathode catalyst layer (CCL) are believed to depend on local humidification [2,4], while the distribution of liquid water may also be influenced by performance drop associated with such degradation [3]. Although some studies have shown the influence of carbon corrosion on liquid water distribution [2,3], the possible reverse effect of liquid water distribution on the CCL degradation requires further investigation. The objective of the present work is to establish a deeper understanding of the cause-and-effect interactions between CCL degradation and liquid water distribution. This is achieved experimentally by carrying out voltage-cycling accelerated stress tests (ASTs) on fuel cells which differ only in the constituent gas diffusion layers (GDLs); namely, SGL 22 BB and a proprietary Avcarb. Three-dimensional X-ray microscopy is used to observe both degradation effects and liquid water distribution at different stages of the ASTs. A relatively rapid operando two-dimensional visualization technique [5] was also used to investigate the differences in liquid water distribution between the two GDLs. The fuel cells imaged are analyzed and exhibit different liquid water distributions, whereby the Avcarb exhibits a higher liquid water condensation close to the CCL, compared to the SGL. Supported by model results, this difference in liquid water distribution is shown to be attributable to the different transport properties of the GDLs. The degradation results, such as the CCL thickness (Fig. 1) show that the Avcarb cell experiences a faster CCL degradation than the SGL cell. Furthermore, the Avcarb liquid water distribution is seen to change with increasing AST cycles in a manner indicating higher vapour phase removal. These results provide insights for GDL design consideration, showing that GDL transport properties may influence liquid water distribution at the electrode with important implications for CCL durability. Acknowledgement Funding for this research was provided by the Natural Sciences and Engineering Research Council of Canada, Ballard Power Systems, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, and Canada Research Chairs. References [1] F. Nandjou, J.-P. Poirot-Crouvezier, M. Chandesris, J.-F. Blachot, C. Bonnaud, and Y. Bultel, “Impact of heat and water management on proton exchange membrane fuel cells degradation in automotive application,” Journal of Power Sources, vol. 326, pp. 182–192, 2016. [2] J. D. Fairweather, D. Spernjak, A. Z. Weber, D. Harvey, S. Wessel, D. S. Hussey, D. L. Jacobson, K. Artyushkova, R. Mukundan, and R. L. Borup, “Effects of cathode corrosion on through-plane water transport in proton exchange membrane fuel cells,” Journal of The Electrochemical Society, vol. 160, no. 9, p. F980, 2013. [3] R. T. White, S. H. Eberhardt, Y. Singh, T. Haddow, M. Dutta, F. P. Orfino, and E. Kjeang, “Four-dimensional joint visualization of electrode degradation and liquid water distribution inside operating polymer electrolyte fuel cells,” Scientific reports, vol. 9, no. 1, p. 1843, 2019. [4] T. Mittermeier, A. Weiß, F. Hasché, and H. A. Gasteiger, “Pem fuel cell start-up/shut-down losses vs relative humidity: the impact of water in the electrode layer on carbon corrosion,” Journal of The Electrochemical Society, vol. 165, no. 16, p. F1349, 2018. [5] F. Aroge, B. Parimalam, J. MacDonald, F. Orfino, M. Dutta, and E. Kjeang, “Analysing operando 2d x-ray transmission images for liquid water distribution in polymer electrolyte fuel cells,” Journal of Power Sources, vol. 564, p. 232820, 2023. Figure 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".