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Record W2152877984 · doi:10.1115/1.4003977

Accelerated Lifetime Testing for Proton Exchange Membrane Fuel Cells Using Extremely High Temperature and Unusually High Load

2011· article· en· W2152877984 on OpenAlexaff
Jianlu Zhang, Chaojie Song, Jiujun Zhang

Bibliographic record

VenueJournal of Fuel Cell Science and Technology · 2011
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBC Innovation Council
Fundersnot available
KeywordsProton exchange membrane fuel cellNafionMaterials scienceMembraneFuel cellsNuclear engineeringChemical engineeringChemistryElectrochemistryElectrodeEngineering

Abstract

fetched live from OpenAlex

In this paper, two testing protocols were developed in order to accelerate the lifetime testing of proton exchange membrane (PEM) fuel cells. The first protocol was to operate the fuel cell at extremely high temperatures, such as 300 °C, and the second was to operate the fuel cell at unusually high current densities, such as 2.0 A/cm2. A PEM fuel cell assembled with a PBI membrane-based MEA was designed and constructed to validate the first testing protocol. After several hours of high temperature operation, the degraded MEA and catalyst layers were analyzed using SEM, XRD, and TEM. A fuel cell assembled with a Nafion 211 membrane-based MEA was employed to validate the second protocol. The results obtained at high temperature and at high load demonstrated that operating a PEM fuel cell under certain extremely high-stress conditions could be used as methods for accelerated lifetime testing.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.219
Teacher spread0.192 · 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".

Quick stats

Citations19
Published2011
Admission routes1
Has abstractyes

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