MétaCan
Menu
Back to cohort
Record W2180981520 · doi:10.1115/etce2002/cae-29012

Modelling and Simulation of PEM Fuel Cells With CO Poisoning

2002· article· en· W2180981520 on OpenAlexaff
J.J. Baschuk, Xianguo Li

Bibliographic record

VenueEngineering Technology Conference on Energy, Parts A and B · 2002
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsProton exchange membrane fuel cellElectrolyteAnodeCathodeTafel equationDesorptionElectrochemistryChemical engineeringChemistryCatalytic reformingAdsorptionThermodynamicsPolymer electrolyte membrane electrolysisMaterials scienceHydrogenMass transferCatalysisElectrodeElectrolysisPhysical chemistryChromatographyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

A polymer electrolyte membrane (PEM) fuel cell has been analyzed by applying the conservation principle to the gas channels, electrode backings, catalyst layers and polymer electrolyte. The conservation equations used are conservation of species, momentum and energy and the Nernst-Planck equation in the electrolyte. Oxygen reduction at the cathode is modeled using the Butler-Volmer equation while the adsorption, desorption and electro-oxidation of hydrogen and CO at the anode are modeled by the Tafel-Volmer and “reactant-pair” mechanism, respectively. Comparison of the anode electrochemical kinetics model to experimental data indicates that CO adsorption kinetics are Temkin. One-dimensional simulation of a PEM fuel cell operating with reformate fuel gas indicates an optimum operating pressure. Preliminary two-dimensional simulation verifies the one-dimensional assumption for mass transfer but indicates that a two-dimensional analysis is necessary for the catalyst layer.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.551

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 head0.013
GPT teacher head0.182
Teacher spread0.169 · 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 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

Citations1
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueEngineering Technology Conference on Energy, Parts A and BSame topicFuel Cells and Related MaterialsFrench-language works237,207