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Record W3115464986 · doi:10.1149/ma2020-02352255mtgabs

An Accelerated Mechanical Stress Test for Evaluating Fatigue Durability of Reinforced Fuel Cell Membranes

2020· article· en· W3115464986 on OpenAlexaffabout
Sandeep Bhattacharya, Alireza Sadeghi Alavijeh, Owen Thomas, Carmen Chuy, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)Simon Fraser University
Fundersnot available
KeywordsMaterials scienceDurabilityMembraneComposite materialIonomerProton exchange membrane fuel cellStress (linguistics)PolymerChemistry

Abstract

fetched live from OpenAlex

For evaluating the durability of membranes in polymer electrolyte fuel cells (PEFCs) within relatively short time, accelerated stress tests (AST) are used for applying chemical and mechanical stressors by means of current density, cell voltage, temperature, and relative humidity (RH) cycling. The U.S. Department of Energy (DOE) standardized RH cycling test is considered as a routine screening test for evaluating the mechanical durability under cyclic mechanical stresses [1]. Due to limitation in diffusion kinetics of water in the membrane, each RH cycle often takes several minutes that consequently restricts the magnitude of the induced mechanical stress. Therefore, conventional mechanical ASTs become time-consuming and expensive, especially as more durable membranes are being adopted. A typical mechanical degradation mitigation strategy is to insert an insulating and chemically-inert reinforcement layer, e.g., a thin microporous expanded polytetrafluoroethylene (ePTFE) mesh in the membrane to improve dimensional stability in response to RH-induced membrane expansion and contraction. The reinforcement layer provides additional mechanical strength and enables the use of thinner and more conductive ionomer that would otherwise have insufficient strength. When tested using mechanical ASTs, reinforced membranes possessed longer lifetime [2,3]. Experimental work on application of ASTs to fuel cell membranes was previously performed [4] where an accelerated membrane durability test (AMDT) was developed to characterize membrane stability when subjected to chemical and mechanical degradation relevant to field operation. In another work [5], mechanical ASTs were performed via in situ RH cycling with longer dry cycles (for maximizing the fatigue stress amplitude) and at a higher temperature than the DOE protocol. Using these conventional protocols, it is expected that tests with reinforced membranes will continue beyond 20,000 cycles (as defined by DOE [1]) without reaching failure. An ex situ blister test method was used for bi-axial fatigue-creep testing by cycling air pressure [6,7]. In this case, the inherent hygroscopic membrane properties, i.e., water uptake and dimensional changes, which are the actual source of in situ fatigue and mechanical degradation in the constrained fuel cell environment, were not considered. In this work, a custom-developed mechanical AST procedure, based in part on the DOE-standardized AST for mechanical membrane degradation [1], was developed and used for evaluating the mechanical fatigue durability of reinforced membranes in a shorter time. Here, mechanical stressors were applied to the membrane using a sustained pressure differential (ΔP) combined with RH cycling at 80 o C in a bi-axial, fuel cell inspired configuration. For validation of the developed method, denoted as ΔP-AMST, ePTFE-reinforced membranes were cycled using 4 min dry (0% RH) and 2 min wet (100% RH) cycles along with a ΔP ranging from 7 to 14 kPa. When the ΔP was applied, a transparent polycarbonate spacer, placed between the cathode and anode, allowed inflation of the membrane by means of a through-thickness hole, as shown in Figure 1. In order to prevent chemical degradation, nitrogen was used as the carrier gas in the ΔP-AMST instead of air, which is used in the DOE method [1]. Depending on the applied ΔP, reinforced membranes failed within ~10 to 10,000 RH cycles, the failure criterion being the loss of ΔP, indicative of major gas leakage through the degraded membrane. Therefore, compared to conventional mechanical ASTs, this novel mechanical AST could be used as a rapid and economical in situ alternative for evaluating the mechanical durability of advanced fuel cell membranes. Acknowledgements This research was supported by Mitacs, Automotive Fuel Cell Cooperation (AFCC), Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Foundation for Innovation, British Columbia Knowledge Development Fund, Western Economic Diversification Canada, and Simon Fraser University. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. References [1] DOE Cell Component Accelerated Stress Test Protocols for PEM Fuel Cells, (2010) https://www1.eere.energy.gov/hydrogenandfuelcells/fuelcells/pdfs/component_durability_profile.pdf [2] Y.H. Lai, C.K. Mittelsteadt, C.S. Gittleman, D.A. Dillard, J. Fuel Cell Sci. Tech. 6 (2009) 021002. [3] D. Spernjak, P.P. Mukherjee, R. Mukundan, J. Davey, D.S. Hussey, D. Jacobson, R.L. Borup, ECS Trans. 33 (2010) 1451. [4] N. Macauley, A. Sadeghi Alavijeh, M. Watson, J. Kolodziej, M. Lauritzen, S. Knights, G. Wang, E. Kjeang, J. Electrochem. Soc. 162 (2015) F98. [5] A. Sadeghi Alavijeh, R.M.H. Khorasany, Z. Nunn, A. Habisch, M. Lauritzen, E. Rogers, G.G. Wang, E. Kjeang, J. Electrochem. Soc. 162 (2015) F1461. [6] D.A. Dillard, Y. Li, J.R. Grohs, S.W. Case, M.W. Ellis, Y.H. Lai, M.K. Budinski, C.S. Gittleman, J. Fuel Cell Sci. Technol., 6(3) (2009) 031014. [7] Y. Li, D.A. Dillard, S.W. Case, M.W. Ellis, Y.H. Lai, C.S. Gittleman, D.P. Miller, J. Power Sources, 194 (2009) 873. Figure 1

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.163
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.281
Teacher spread0.232 · 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 teacher head, 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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Citations1
Published2020
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