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Record W2036142233 · doi:10.1002/fuce.200300004

A Review of Mathematical Models for Hydrogen and Direct Methanol Polymer Electrolyte Membrane Fuel Cells

2004· review· en· W2036142233 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFuel Cells · 2004
Typereview
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsDuPont (Canada)Royal Military College of CanadaQueen's University
Fundersnot available
KeywordsElectrolyteFuel cellsMembraneMethanol fuelHydrogenProton exchange membrane fuel cellElectrochemistryPolymerMaterials scienceDiffusionTransport phenomenaMathematical modelMethanolChemical engineeringChemistryComputer scienceMechanicsThermodynamicsElectrodeEngineeringPhysicsOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract This paper presents a review of the mathematical modeling of two types of polymer electrolyte membrane fuel cells: hydrogen fuel cells and direct methanol fuel cells. Models of single cells are described as well as models of entire fuel cell stacks. Methods for obtaining model parameters are briefly summarized, as well as the numerical techniques used to solve the model equations. Effective models have been developed to describe the fundamental electrochemical and transport phenomena occurring in the diffusion layers, catalyst layers, and membrane. More research is required to develop models that are validated using experimental data, and models that can account for complex two‐phase flows of liquids and gases.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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