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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 OpenAlex
Farisa Forouzandeh, Dustin Banham, Fangxia Feng, Xiaoan Li, Siyu Ye, Viola Birss

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.
fundA Canadian funder is recorded on the work.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.378

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 head0.010
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