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Record W1973473860 · doi:10.1115/fuelcell2006-97027

PEM Unit Cell Model Considering Additional Reactions

2006· article· en· W1973473860 on OpenAlexaff
Brian Wetton, Gwang-Soo Kim, Keith Promislow, Jean St‐Pierre

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBallard Power Systems (Canada)University of British Columbia
Fundersnot available
KeywordsAnodeCathodeMechanicsHydrogenIsothermal processMaterials scienceMass transportCrossoverProton exchange membrane fuel cellElectrochemistryCarbon fibersChemistryElectrodeThermodynamicsMembraneComputer sciencePhysicsComposite material

Abstract

fetched live from OpenAlex

A computational model is developed for a PEM unit cell capable of describing the reactions that occur in the cell in understoich conditions. Such conditions can occur as a result of reactant supply system failure (blockage, leaks, system control, etc.). The model applies to cells with straight channels, and mass transport in the MEA (membrane crossover as well as transport through the GDE) in the channel cross-plane is described only in an average sense assuming linear diffusive mechanisms. Several other major assumptions are made, the most significant being that the cell is always at saturated conditions and is taken to be isothermal. Several electrochemical and mass transport coefficients are not available in the literature and “best guesses” are taken. The results of the model are not yet validated experimentally. However, it is the first model proposed that captures these phenomena in a comprehensive way at the local level and also couples the phenomena through channel flow. Cathode understoich results show the expected Hydrogen evolution at the cathode. Anode understoich results show anode Carbon oxidation. An interesting third run is shown where at low currents, a partial anode understoich condition occurs where the cell voltage remains positive, but the anode is starved of Hydrogen near outlet. Carbon corrosion at the cathode occurs in this case.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.010
GPT teacher head0.174
Teacher spread0.164 · 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 designSimulation or modeling
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

Citations2
Published2006
Admission routes1
Has abstractyes

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