MétaCan
Menu
Back to cohort
Record W2025976770 · doi:10.1149/05801.1791ecst

In-Situ Measurement of Oxygen Partial Pressure in the Cathode Flow Field with a Hydrophilic Surface

2013· article· en· W2025976770 on OpenAlexaff
Shin‐ichi Hirano, Michael Potocki, George Saloka, Steve Palluconi, James Crafton

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsFord Motor Company (Canada)
Fundersnot available
KeywordsPartial pressureFluorophoreCathodeMaterials sciencePolymerQuenching (fluorescence)OxygenAnalytical Chemistry (journal)Oxygen sensorProton exchange membrane fuel cellLimiting oxygen concentrationChemical engineeringComposite materialChemistryFluorescenceMembraneOpticsChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Cathode oxygen concentration is vital for the performance of proton exchange membrane fuel cells (PEMFC). A novel method to directly detect oxygen partial pressure in the cathode flowfield has been developed utilizing fluorophore molecules which are sensitive to oxygen quenching. A platinum porphyrin based fluorophore is used with a polymer binder to form the fluorophore layer that is exposed to the cathode gas flow field in the visualization cell. In this study, poly-heptafluoro-n-butly, methacrylate-co-hexafluroisopropyl, and methacrylate (FIB polymer) were used as the binder to obtain a proper range of quenching rate. Thus, the intensity of fluorescent luminescence of this fluorophore layer covers 7 kPa to 53 kPa oxygen partial pressure concentration. Also, this material composition exhibits acceptable temperature sensitivity between 40 to 90 degrees C. The polymer binder modification described in this report enabled accurate in-situ oxygen partial pressure measurements to cover typical operating conditions of an automotive PEMFC.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.258

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 head0.009
GPT teacher head0.186
Teacher spread0.176 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueECS TransactionsSame topicFuel Cells and Related MaterialsFrench-language works237,207