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Record W357822786

A structure-based model for cathode catalyst layer of polymer electrolyte membrane fuel cell

2007· dissertation· en· W357822786 on OpenAlexfundno aff
Jianfeng Liu

Bibliographic record

VenueSummit (Simon Fraser University) · 2007
Typedissertation
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersMitacs
KeywordsElectrolyteCathodeFuel cellsProton exchange membrane fuel cellMaterials scienceLayer (electronics)MembranePolymerChemical engineeringCatalysisComposite materialEngineeringElectrodeChemistryElectrical engineeringOrganic chemistryPhysical chemistry
DOInot available

Abstract

fetched live from OpenAlex

A structure-based performance model for Cathode Catalyst Layers (CCLs) of Polymer Electrolyte Membrane Fuel Cells (PEMFCs) is presented. A CCL is the major competitive ground for mass transport, electrochemical reaction, and vaporization in a PEMFC. Analytical solutions for the case of fast proton transport have revealed that the CCL plays a vital role in the conversion of liquid water to vapor and in regulating water fluxes towards Polymer Electrolyte Membrane (PEM) and Gas Diffusion Layer (GDL). Critical values of proton conductivity and oxygen transport coefficient are introduced to distinguish different regimes of operation for these transport processes. Subsequently, the role of the porous structure and of liquid water accumulation for the performance of CCL in PEMFCs is explored. The non-linear spatial coupling between liquid water accumulation and oxygen depletion triggers critical effects and bistability in current-voltage response curves. Stability diagrams are proposed as novel tools for assessing CCL performance.

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)0.000
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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