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Record W2068796944 · doi:10.1149/1.3356939

Characterization of the Degree of Ru Crossover and Its Performance Implications in Polymer Electrolyte Membrane Fuel Cells

2010· article· en· W2068796944 on OpenAlexafffund
Tommy Cheng, Nengyou Jia, Ping He

Bibliographic record

VenueJournal of The Electrochemical Society · 2010
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBallard Power Systems (Canada)
FundersBallard Power Systems
KeywordsAnodeElectrolyteCrossoverCathodeMaterials scienceMembrane electrode assemblyCharacterization (materials science)PolymerProton exchange membrane fuel cellChemical engineeringFuel cellsCyclic voltammetryDurabilityChemistryElectrochemistryNanotechnologyElectrodeComputer scienceComposite materialPhysical chemistry

Abstract

fetched live from OpenAlex

The durability of the polymer electrolyte membrane fuel cell is identified as one of the major limiting factors for the wide commercialization of fuel cells. In particular, the phenomenon of Ru crossover from the anode to the cathode has severe performance implications. In the present investigation, a facile and cost-effective in situ diagnostic method was developed to quantify Ru crossover and to predict its performance impact. The scheme was validated with neutron activation analysis (NAA). A proprietary anode accelerated stress test was used to cause various degrees of Ru crossover, and the end-of-life cathode catalyst layers were characterized by cyclic voltammetry, X-ray diffraction, and NAA. The observed characterization relationships provided a mechanistic understanding of Ru crossover and were demonstrated to be functional as an in situ diagnostic method.

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)0.000
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
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 head0.006
GPT teacher head0.184
Teacher spread0.179 · 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

Citations23
Published2010
Admission routes2
Has abstractyes

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