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Record W2737713942 · doi:10.1149/08008.0175ecst

Investigating the Effect of Non-Uniform Microporous Layer Intrusion on Oxygen Transport in Dry and Partially Saturated Polymer Electrolyte Membrane Fuel Cell Gas Diffusion Layers

2017· article· en· W2737713942 on OpenAlex
Andrew Wong, Aimy Bazylak

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

VenueECS Transactions · 2017
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInletSaturation (graph theory)DiffusionOxygenGaseous diffusionMicroporous materialChemistryElectrolyteOxygen transportPermeability (electromagnetism)MembraneMaterials scienceThermodynamicsGeology

Abstract

fetched live from OpenAlex

Pore network modelling was utilized to simulate the oxygen transport behavior and water saturation within stochastically generated gas diffusion layers (GDLs) at various liquid water inlet conditions. The oxygen diffusion coefficient in dry conditions was found to linearly decrease as a function of the MPL intrusion depth into the GDL. In partially saturated conditions, increasing MPL intrusion minimized the fluctuations in both oxygen diffusion coefficient and breakthrough saturation over the range of sparse inlet conditions (7% inlet face coverage) to flooded inlet conditions (80% inlet face coverage). Breakthrough saturation was highly dependent on MPL intrusion depth with flooded liquid water inlet conditions compared to sparse liquid water inlet conditions. This study suggests that when the GDL is invaded by liquid water through cracks in the MPL, preferential MPL configurations exist for improving oxygen transport and minimizing substrate saturation given particular inlet conditions.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.597

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 head0.005
GPT teacher head0.199
Teacher spread0.194 · 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