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Record W2263957872 · doi:10.1002/fuce.201500138

Impact of Ionomer Content on Proton Exchange Membrane Fuel Cell Performance

2015· article· en· W2263957872 on OpenAlex

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

VenueFuel Cells · 2015
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNafionIonomerProton exchange membrane fuel cellAnodeMaterials scienceCathodic protectionElectrodeMembrane electrode assemblyPolarization (electrochemistry)CathodeElectrocatalystChemical engineeringComposite materialAnalytical Chemistry (journal)Fuel cellsChemistryElectrochemistryChromatographyPolymerEngineering

Abstract

fetched live from OpenAlex

Abstract The effect of Nafion ionomer content on performance of a proton exchange membrane (PEM) fuel cell operated with home‐made anodic and cathodic electrodes fabricated from a novel metal organic framework (MOF) derived Pt‐based electrocatalyst was investigated via numerical simulation and experimental measurement. First, the parameter sensitivity analysis was performed to identify the most influential parameters of the model. Then, these parameters were calibrated for different fuel cell designs investigated in the current study by employing the corresponding experimental data. Afterwards, the calibrated model was used to examine the impact of Nafion content in the catalyst layer of home‐made electrodes. Finally, the qualitative trend predicted by this model was experimentally surveyed by varying the Nafion content between 10–50 wt.% in the catalyst layer of home‐made electrodes. At the anode side, the performance of home‐made electrode in a PEM fuel cell demonstrated small dependency on Nafion content. For the cathodic home‐made electrode, Nafion content was found to affect the PEM fuel cell performance more strongly. Although the model could correctly capture the impact of Nafion content on calculated polarization curves, the model predicted optimum values significantly deviate from the experimental results. This was related to the several simplifications made during model development.

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 score0.326
Threshold uncertainty score0.773

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)0.0010.001

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 head0.035
GPT teacher head0.222
Teacher spread0.187 · 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