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Fuel cell membrane durability impacts of incidental non-metallic particle deposition – Part 2: Failure prevention strategies

2025· article· en· W4412798146 on OpenAlexafffund
MohammadAmin Bahrami, Nitish Kumar, Yixuan Chen, Olivia C. Lowe, Francesco P. Orfino, Monica Dutta, Michael Lauritzen, Erin Setzler, Alexander L. Agapov, Erik Kjeang

Bibliographic record

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBallard Power Systems (Canada)Simon Fraser University
FundersWestern Economic Diversification CanadaBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationW. L. Gore and AssociatesBallard Power Systems
KeywordsDurabilityMaterials scienceFuel cellsDeposition (geology)Particle (ecology)MetalMetallurgyForensic engineeringChemical engineeringEngineeringComposite materialGeology

Abstract

fetched live from OpenAlex

This two-part article series examines the impacts of incidental non-metallic particle deposition on fuel cell membrane durability. Part 1 investigates the effect of particle type, while Part 2 focuses on mitigation approaches. In this part (Part 2), the behavior of flat, solid particles embedded at the membrane and cathode catalyst layer interface, shown to be harmful in Part 1, is studied experimentally in greater detail. These particles, which can originate from fuel cell components or fabrication machinery debris, are found to compromise membrane durability by forming cavities within the membrane electrode assembly (MEA) that promote cracking and creeping. The role of microporous layer (MPL) properties as the adjacent layer is then analyzed in relation to local deformation of MEA components in the presence of a particle. Numerical simulations show that MPL elasticity and plastic yield stress influence the likelihood of membrane failure near particles. Based on these insights, mitigation strategies are proposed. Numerical and experimental results demonstrate that applying pre-pressure to the MEA alters component deformation in a way that reduces membrane stress during operation and enhances fuel cell durability.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.210
Teacher spread0.206 · 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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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