Polymer Electrolyte Fuel Cell Degradation Investigations Using X-Ray Computed Tomography
Bibliographic record
Abstract
On-going research is aimed at commercializing low temperature fuel cell technology systems as zero emission alternatives for automotive applications in order to reduce greenhouse gas emissions and air pollution. These systems use polymer electrolyte fuel cells (PEFCs) to generate electricity via an electrochemical process using hydrogen and ambient air (oxygen) to produce water. Advantages of PEFCs include quick start-up time, low operating temperature, low weight, high efficiency, and relatively simple design. An important area of current research is the identification of factors which affect fuel cell performance degradation during operation and ultimately, its durability. A technique that has yielded new insights in the investigation and identification of failure modes in fuel cells is lab-based X-ray computed tomography (XCT), which is most advantageous due to its on-demand availability. The Fuel Cell Research Laboratory (FCReL) at Simon Fraser University currently operates Canada’s only facility for multi-length scale XCT, comprising of two state-of-the-art laboratory-based XCT scanners from Carl Zeiss X-ray Microscopy (Zeiss Xradia 520 Versa and 810 Ultra) with complementary resolution and field of view capabilities. This unique combination offers unprecedented access to investigations at multi length scales; with an ability to probe fuel cell components at the micro as well as the nano scale. Figure 1 illustrates the fuel cell holder and its orientation with respect to the X-ray beam as well as an exploded view of the miniature fuel cell design. An overview of recent fuel cell degradation investigations at FCReL using the XCT technique will be shown. The XCT based workflow facilitates determination and quantification of material structure and properties changes resulting from degradation stresses associated with operational parameters such as temperature, relative humidity, and voltage. The non-destructive nature of lab-based XCT visualization coupled with the ability to scan the same fuel cell multiple times without inducing damage [1] has enabled detailed studies of fuel cell degradation evolution in four dimensions (3D space, 1D time) [2 - 4]. The new knowledge gained from this procedure has led to root cause identification with respect to membrane and catalyst layer crack initiation and propagation [5 - 7], sealing issues [8,9], and subsequent mitigation toward enhanced fuel cell durability. Acknowledgement This research was supported by the Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, Western Economic Diversification Canada, Canada Research Chairs, and Ballard Power Systems. References: [1] R.T. White, M. Najm, M. Dutta, F.P. Orfino, E. Kjeang, J. Electrochem. Soc. 163 (2016) F1206-F1208 [2] R.T. White, A. Wu, M. Najm, F.P. Orfino, M. Dutta, E. Kjeang, J. Power Sources 350 (2017) 94-102 [3] R. T. White, S. H. Eberhardt, Y. Singh, T. Haddow, M. Dutta, F. P. Orfino, E. Kjeang, Scientific Reports, (2019) 9:1843 [4] R. T. White, D. Ramani, S. H. Eberhardt, M. Najm, F. P. Orfino, M. Dutta, and E. Kjeang, J. Electrochem Soc, 166 (2019) F914-F925 [5] Y. Singh, R. T. White, M. Najm, T. Haddow, V. Pan, F. P. Orfino, M. Dutta, and E. Kjeang, J. Power Sources, 412 (2019) 224 [6] D. Ramani, Y. Singh, R. T. White, M. Wegener, F. P. Orfino, M. Dutta, and E. Kjeang, International Journal of Hydrogen Energy, 45 (2020) 10089-10103 [7] D. Ramani, Y. Singh, R. T. White, T. Haddow, M. Wegener, F. P. Orfino, L. Ghassemzadeh, M. Dutta, and E. Kjeang, Electrochimica Acta 380 (2021) 138194 [8] Y. Chen, Y. Singh, D. Ramani, F. P. Orfino, M. Dutta, and E. Kjeang, J. Power Sources, 520 (2022) 230674 [9] Y. Chen, Y. Singh, D. Ramani, F. P. Orfino, M. Dutta, and E. Kjeang, J. Power Sources, 520 (2022) 230673 [10] J. Stoll, F. P. Orfino, M. Dutta, and E. Kjeang, J. Electrochem Soc, (2021) 168 024516 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".