Optimized Decal Transfer Method for the Mitigation of Incidental Particle Deposition at the Interface of Proton Exchange Membranes and Catalyst Layers
Bibliographic record
Abstract
The membrane electrolyte assembly (MEA) is the key component of a proton exchange membrane fuel cell (PEMFC). The MEA usually consists of gas diffusion layers as outer layers to the inner catalyst coated membrane (CCM). There are various methods to prepare CCMs and decal transfer is currently a common method which was first introduced by Wilson and Gottesfeld [1] and further developed by other researchers [2]–[4]. The initial step of this method is that the catalyst ink is coated onto an intermediate substrate material creating a catalyst coated film (CCF). This step is followed by a transfer of the active layer onto the membrane by hot pressing the membrane and CCF between heated press platens maintained at a specific high temperature for an optimized time and pressure to ensure bonding. Extensive studies on the procedure of decal transfer, substrate material and its preparation, catalyst solvents, etc. have increased the transfer yield of decal transfer to more than 95% [5]. Additionally, in the last decade, industrial development has reduced its cost; however, the total cost for fuel cell manufacturing is still relatively high. One reason for this high production cost is the contamination sensitivity of the CCMs by external particles that can potentially be detrimental to fuel cell operation [6]. This requirement necessitates the use of cleanrooms and quality control equipment to prevent contaminants entering the manufactured components, thus increasing the overall costs. The purpose of the present research is to improve the understanding of the interactions between foreign contaminants and the manufacturing process in the context of MEA production quality. The specific objectives are to i) understand the impact of external particles on the catalyst layer decal transfer process and ii) improve the robustness of the decal transfer method in the presence of external particles. This research investigates the impact of incidental external particles that may be found on the membrane surface or the CCF prior to hot pressing. 60µm Silica microspheres (Si-M) were selected as a representative of solid particles and CCMs with purposely introduced Si-Ms were fabricated and several decal transfer methods and support materials were tested and imaged using the X-ray computed tomography (XCT) technique to analyze the impact on the fuel cell integrity and operation at the presence of the Si-M. While regular decal transfer protocols result in excessive membrane thinning in the presence of these particles, it was observed that by changing the rate of applied pressure and using alternative support materials when transferring the cathode catalyst onto a half-coated membrane, it was possible to reduce membrane thinning under the particles by more than 20% while maintaining transfer quality and cell performance (Fig. 1). In addition, it was observed that although anisotropic mechanical properties of the membrane can adversely affect the CCM topography after the decal transfer, a tuned protocol is able to prevent unwanted deformations and potential stress concentrations. Overall, it is envisioned that the outcomes of this work may enable relaxed quality control measures and manufacturing site cleanroom standards by reducing the potential effects of external particles on MEA production quality. Acknowledgements 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, Ballard Power Systems, and W.L. Gore & Associates. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. Keywords: fuel cell; membrane durability; X-ray computed tomography; decal transfer; manufacturing References Wilson, M. S. & Gottesfeld, S. Thin-film catalyst layers for polymer electrolyte fuel cell electrodes. J. Appl. Electrochem. 22, 1–7 (1992). Shahgaldi, S., Alaefour, I. & Li, X. Impact of manufacturing processes on proton exchange membrane fuel cell performance. Appl. Energy 225, 1022–1032 (2018). Cho, H. J. et al. Development of a novel decal transfer process for fabrication of high-performance and reliable membrane electrode assemblies for PEMFCs. Int. J. Hydrogen Energy 36, 12465–12473 (2011). Thanasilp, S. & Hunsom, M. Effect of MEA fabrication techniques on the cell performance of Pt-Pd/C electrocatalyst for oxygen reduction in PEM fuel cell. Fuel 89, 3847–3852 (2010). Liang, X., Pan, G., Xu, L. & Wang, J. A modified decal method for preparing the membrane electrode assembly of proton exchange membrane fuel cells. Fuel 139, 393–400 (2015). James, B. D., Moton, J. M. & Colella, W. G. Mass Production Cost Estimation of Direct H2 PEM Fuel Cell Systems for Transportation Applications: 2018 Update. ASME 2014 12th Int. Conf. Fuel Cell Sci. Eng. Technol. collocated with ASME 2014 8th Int. Conf. Energy Sustain. V001T07A002–V001T07A002 (2018). 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".