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Record W1982994100 · doi:10.1115/1.2821599

Reaction Kinetics at the Triple-Phase Boundary in PEM Fuel Cells

2008· article· en· W1982994100 on OpenAlexaff
Peter Berg, Arian Novruzi, Oleg Volkov

Bibliographic record

VenueJournal of Fuel Cell Science and Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of OttawaOntario Tech University
Fundersnot available
KeywordsProton exchange membrane fuel cellPorosityNonlinear systemDiffusionMechanicsPartial differential equationThermodynamicsGaseous diffusionChemistryMaterials scienceMembranePhysical chemistryPhysicsComposite material

Abstract

fetched live from OpenAlex

A mathematical model is developed to describe the reaction dynamics in the vicinity of the triple-phase boundary (TPB), which is an important part of the pore scale structure of the catalyst layer in proton exchange membrane fuel cells. The model incorporates coupled diffusion, migration, and reaction phenomena of the chemical components in an undersaturated air pore and ionomer. One challenging feature of the work is the description of the TPB by a system of nonlinear partial differential equations (PDEs), coupling bulk, and surface-diffusion phenomena, which offers an approach to study the rarely investigated proton surface diffusion along the air pore surface. A numerical technique is implemented, taking into account the particular form of the domain, in order to solve the nonlinear PDE system efficiently. Several numerical results are discussed, including a sensitivity analysis with respect to the physical reference case and geometric parameters. The results indicate that surface diffusion might play a major role for the reaction kinetics, but only if the air pore is void of liquid water. In contrast, the formation of liquid water in the gas pores will turn surface diffusion into bulk diffusion, with the latter resembling the Grotthus mechanism.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

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