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Record W2322751108 · doi:10.1149/06403.0341ecst

Effect of Electrode Patterning on PEM Fuel Cell Performance using Ink-Jet Printing Method

2014· article· en· W2322751108 on OpenAlexafffund
Shantanu Shukla, Kailyn Domican, Marc Secanell

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Alberta
FundersCanada School of Energy and EnvironmentNatural Sciences and Engineering Research Council of CanadaEnergy Foundation
KeywordsElectrodeMaterials scienceLimiting currentLimitingInkwellOptoelectronicsPolarization (electrochemistry)NanotechnologyFuel cellsInkjet printingComposite materialChemical engineeringMechanical engineeringChemistryElectrochemistryEngineering

Abstract

fetched live from OpenAlex

The suitability of inkjet printing technology for patterning fuel cell electrodes was investigated. A study on resolution of the inkjet printer showed that micro-scale distinguishable patterns can be fabricated within a spacing of 300 microns. The performance of the patterned and non-patterned electrodes were compared from the polarization plot obtained at a cell temperature of 80◦C and 70% RH with an estimated cathodic loading of 0.075 mg/cm2. Preliminary results show that under the current operating conditions, not much change in performance is observed, however the patterned electrodes have the potential to achieve higher limiting currents when the masstransport effects are dominant and is being currently investigated.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
Teacher spread0.212 · 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 designBench or experimental
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

Citations20
Published2014
Admission routes2
Has abstractyes

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