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Record W2274187003 · doi:10.1149/ma2014-02/21/1297

Fatigue Testing of Fuel Cell Membranes: Comparison of In-Situ and Ex-Situ Techniques

2014· article· en· W2274187003 on OpenAlexaffabout
Alireza Sadeghi Alavijeh, Ramin M.H. Khorasany, Zachary R. Nunn, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProton exchange membrane fuel cellMaterials scienceMembraneStack (abstract data type)Chemical energyRelative humidityIn situComposite materialScanning electron microscopeChemistry

Abstract

fetched live from OpenAlex

Increasing the lifetime and reliability of proton exchange membrane fuel cells (PEMFCs) is one of the main challenges facing the fuel cell industry. Under automotive operating conditions, the membrane in PEMFCs is subjected to chemical and mechanical degradation, which gradually leads to loss in performance and subsequent failure. The US Department of Energy (DOE) has developed standardized protocols for in-situ chemical and mechanical accelerated stress tests (ASTs) [1]. The decay in membrane properties under pure chemical, pure mechanical, and combined chemical – mechanical AST [2-4] were recently evaluated. In the area of mechanical membrane degradation, material fatigue is expected to dominate, and an ex-situ fatigue based AST technique was recently developed by our group [5]. The objective of the present work is to compare the action of the ex-situ fatigue AST to that of the more established in-situmechanical AST protocol. For this purpose, fatigue lifetime, failure modes, and decay in mechanical properties were investigated and compared for both AST techniques. In-situ mechanical AST was conducted on a five-cell research-scale fuel cell stack by applying wet–dry cycles from 0% to 90% relative humidity under a modified DOE mechanical AST protocol. CCM samples were periodically extracted from the stack after certain numbers of AST cycles (every 4,000 cycles) and replaced by fresh cells. In order to investigate the formation of mechanical damage in the membrane, leak tests followed by a systematic microstructural study using scanning electron microscopy (SEM) were applied on the extracted samples. Post-mortem analysis on the degraded samples using an infrared camera showed traces of mechanical defects facilitating gas crossover through the membrane and leading to failure, as depicted in Figure 1. The decay in mechanical properties was evaluated through conducting tensile and expansion experiments on the degraded samples at different AST cycles, in accordance with our recently established CCM characterization procedures [6]. The ex-situ fatigue AST experiments, on the other hand, were applied on fresh CCM specimens utilizing fatigue stresses via a dynamic mechanical analyzer (DMA) equipped with an environmental chamber. Systematic fatigue experiments in our group, proved the capability of cyclic loadings in order to benchmark the mechanical durability of the materials. It was observed that membrane fatigue life is a strong function of temperature and relative humidity [5]. Employing the outcomes of the baseline fatigue data, approximate CCM fatigue lifetimes were extrapolated and predicted at the desired test conditions. Depending on the total fatigue lifetime, fatigue experiments were interrupted at different fractions of the CCM lifetime in conjunction with the corresponding in-situ extractions. In a similar manner, tensile and expansion experiments were performed on ex-situ fatigue extracted specimens to evaluate the decay in mechanical properties under cyclic loading. The results of the two methods are comprehensively compared and utilized to shed light on the overall fundamental understanding of the pure mechanical membrane degradation mechanism and the associated CCM fatigue lifetime. The capabilities of the ex-situfatigue experiment as a rapid, inexpensive mechanical AST are discussed. Figure 1. Formation of leak observed during the in-situmechanical AST. The bright region captured by an infrared camera indicates the main leak location near the inlet. Acknowledgements: This research was supported by Ballard Power Systems and the Natural Sciences and Engineering Research Council of Canada through an Automotive Partnership Canada grant. References: [1] http://www1.eere.energy.gov/hydrogenandfuelcells/mypp [2] Y.P. Patil, et al., J Membrane Sci. 356, 7, 2010. [3] J. Kang and J. Kim, Int J Hydrogen Energ, 35, 13125, 2010. [4] C. Lim, et al., J Power Sources, 257, 102, 2014. [5] R. Khorasany et al., J Power Sources, (under review). [6] M.A. Goulet, et al., J Power Sources,234, 38-47, 2013.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.240
Teacher spread0.220 · 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
Published2014
Admission routes2
Has abstractyes

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Same venueECS Meeting AbstractsSame topicFuel Cells and Related MaterialsFrench-language works237,207