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Record W4309813911 · doi:10.1149/ma2022-02401482mtgabs

Optimized Decal Transfer Method for the Mitigation of Incidental Particle Deposition at the Interface of Proton Exchange Membranes and Catalyst Layers

2022· article· en· W4309813911 on OpenAlexaffabout
Amin Bahrami, Nitish Kumar, Yixuan Chen, Francesco P. Orfino, Monica Dutta, Erin Setzler, Alexander Agapov, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProton exchange membrane fuel cellMembraneMaterials scienceMembrane electrode assemblyChemical engineeringParticle (ecology)Substrate (aquarium)CatalysisElectrolyteProcess engineeringChemistryEngineeringElectrodeOrganic chemistry

Abstract

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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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.011
GPT teacher head0.254
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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Same venueECS Meeting Abstracts→Same topicFuel Cells and Related Materials→French-language works237,207→