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Record W2099030035 · doi:10.1149/05801.1739ecst

Corrosion Study of Mesoporous Carbon Supports for Use in PEM Fuel Cells

2013· article· en· W2099030035 on OpenAlexafffund
Farisa Forouzandeh, Dustin Banham, Fangxia Feng, Xiaoan Li, Siyu Ye, Viola Birss

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaBallard Power Systems
KeywordsCorrosionMicroporous materialThermogravimetric analysisMaterials scienceCarbon fibersMesoporous materialChemical engineeringProton exchange membrane fuel cellNuclear chemistryFuel cellsChemistryMetallurgyComposite materialOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

In this study, the corrosion resistance of two ordered, high surface area, mesoporous carbons (OMCs) were evaluated for PEM fuel cell applications, in comparison with microporous Vulcan carbon (VC). Using a hexagonal mesoporous silica as a hard template, the OMCs were synthesized using sucrose and anthracene as the carbon precursors, denoted as OMC-S and OMC-A, respectively. The corrosion testing protocol involved a potential cycling-step sequence between 1.4 V for 50 s and 0.8 V for 10 s, for a total of 18 cycles, all in room temperature 0.5 M H 2 SO 4 . The corrosion resistance of the carbons is found to be VC > OMC-A > OMC-S, which correlates with their degree of graphitization, as determined by X-ray diffraction and thermogravimetric analysis.

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)0.000
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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