Impact of Missing Cathode Catalyst Layer Areas on Performance and Durability in PEM Fuel Cells
Bibliographic record
Abstract
High throughput and product quality are essential for the scalable production of cost-effective polymer electrolyte membrane fuel cells (PEMFCs). Therefore, it is important to understand the possible implications of various material defects that could appear in the manufacturing process. During the fabrication and assembly of catalyst-coated membranes (CCM)s, the catalyst layers (CL)s may contain void regions of partially missing material due to deficient deposition or unintentional removal, which could affect fuel cell performance and durability [1], [2]. For instance, CL cracks have been shown to expand and propagate into more harmful membrane cracks [3]–[5]. In addition, local thickness differences in CCMs arising from missing CL sections or deficiencies in other components could result in local stress concentration and susceptibility of membrane pinhole formation [6], [7]. Therefore, in general, a missing section of the CL area or other similar irregular features in the CL of a CCM may imply categorizing these CCMs as defective (i.e., scrap) and excluding them for fuel cell assembly. However, on the contrary, M. Kim et al. found increased cell performance for cracked CCM via tensile forces (within the elastic strain region) due to improved mass transport and decreased membrane resistance [8]. Consequently, to improve the understanding of CCM defects, the present work investigates how different missing cathode catalyst layer (CCL) areas affect the PEMFC performance and durability. In more detail, we prepared via ultrasonic spray coating 25 cm 2 active area MEAs with 4.0, 5.9, and 8.5% missing CCL areas obtained by masking (as shown in the Figure), and compared these to defect-free CCL baselines. The results of this study feature a comprehensive assessment of the fuel cell performance of the defective MEAs compared to the baseline MEAs. This includes extraction of the membrane and charge transfer resistances from the missing CCL areas via medium- and high-frequency equivalent circuit modeling of in-situ electrochemical impedance spectroscopy (EIS) data at a current density of 0.1 A/cm 2 and contact, membrane, charge transfer, and mass transfer resistances at a current density of 1 A/cm 2 . Findings on the influences on the electrochemical surface area, hydrogen cross-over current density, and double-layer capacitance from such missing CCL area will also be presented. Results from chemical/mechanical and electrochemical cycling tests will also be shown regarding the effect on durability from the missing CCL area. The results from this work may benefit the economy of scale for high-volume fuel cell manufacturing by reducing unnecessary CCM replacements and materials waste by providing a threshold for an acceptable missing CCL area. Acknowledgements Funding for this research was provided by National Research Council Canada’s Clean and Energy-efficient Transportation (CEET) program and Canada Research Chairs. References [1] M. P. Arcot, K. Zheng, J. McGrory, M. W. Fowler, and M. D. Pritzker, “Investigation of catalyst layer defects in catalyst-coated membrane for PEMFC application: Non-destructive method,” Int. J. Energy Res. , vol. 42, no. 11, pp. 3615–3632, 2018, doi: https://doi.org/10.1002/er.4107. [2] A. Phillips, M. Ulsh, K. C. Neyerlin, J. Porter, and G. Bender, “Impacts of electrode coating irregularities on polymer electrolyte membrane fuel cell lifetime using quasi in-situ infrared thermography and accelerated stress testing,” Int. J. Hydrog. Energy , vol. 43, no. 12, pp. 6390–6399, Mar. 2018, doi: 10.1016/j.ijhydene.2018.02.050. [3] R. T. White, A. Wu, M. Najm, F. P. Orfino, M. Dutta, and E. Kjeang, “4D in situ visualization of electrode morphology changes during accelerated degradation in fuel cells by X-ray computed tomography,” J. Power Sources , vol. 350, pp. 94–102, May 2017, doi: 10.1016/j.jpowsour.2017.03.058. [4] J. Stoll, F. P. Orfino, M. Dutta, and E. Kjeang, “Four-Dimensional Identical-Location X-ray Imaging of Fuel Cell Degradation during Start-Up/Shut-Down Cycling,” J. Electrochem. Soc. , vol. 168, no. 2, p. 024516, Feb. 2021, doi: 10.1149/1945-7111/abe56b. [5] D. Ramani et al. , “Four-dimensional in situ imaging of chemical membrane degradation in fuel cells,” Electrochimica Acta , vol. 380, p. 138194, Jun. 2021, doi: 10.1016/j.electacta.2021.138194. [6] F. E. Hizir, S. O. Ural, E. C. Kumbur, and M. M. Mench, “Characterization of interfacial morphology in polymer electrolyte fuel cells: Micro-porous layer and catalyst layer surfaces,” J. Power Sources , vol. 195, no. 11, pp. 3463–3471, Jun. 2010, doi: 10.1016/j.jpowsour.2009.11.032. [7] Y.-H. Cho, H.-S. Park, J. Kim, Y.-H. Cho, S. W. Cha, and Y.-E. Sung, “The Operation Characteristics of MEAs with Pinholes for Polymer Electrolyte Membrane Fuel Cells,” Electrochem. Solid-State Lett. , vol. 11, no. 8, p. B153, Jun. 2008, doi: 10.1149/1.2937450. [8] S. M. Kim et al. , “High-performance Fuel Cell with Stretched Catalyst-Coated Membrane: One-step Formation of Cracked Electrode,” Sci. Rep. , vol. 6, no. 1, Art. no. 1, May 2016, doi: 10.1038/srep26503. 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".