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Record W2977435499 · doi:10.1149/09208.0801ecst

Balancing Reactant Transport and PTL-CL Contact in PEM Electrolyzers by Optimizing PTL Design Parameters via Stochastic Pore Network Modeling

2019· article· en· W2977435499 on OpenAlex
Jason Keonhag Lee, 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 · 2019
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPorosityMaterials scienceElectrolyteElectrolysisChemical engineeringWettingSurface roughnessComposite materialChemistryElectrode

Abstract

fetched live from OpenAlex

The impacts of sintered titanium powder diameter and porous transport layer (PTL) porosity on reactant transport and PTL-catalyst layer (CL) contact in the polymer electrolyte membrane (PEM) electrolyzer were studied using stochastic generation and a pore network model. Enhanced reactant transport was established with increased powder diameter and porosity, observed through increases in single- and two-phase permeabilities. Compared to increasing the powder diameter, increasing the PTL porosity dominated increases in permeabilities, especially at higher porosities (e > 40%). However, we observed a trade-off whereby increasing the powder diameter led to increased surface roughness at the PTL-CL interface. High roughnesses were observed at porosities > 40%. In conclusion, the powder diameter and porosity must be strategically selected for the desired target operating conditions of the PEM electrolyzer.

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 categoriesMeta-epidemiology (narrow)
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 score0.729
Threshold uncertainty score1.000

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 head0.006
GPT teacher head0.171
Teacher spread0.165 · 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