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Record W2006953628 · doi:10.1149/1.2981877

Enhancing the Performance of Non-noble Metal Catalysts for the Reduction of O2 in PEM Fuel Cells: is the Adsorption of Iron the Limiting Factor for Increasing the Site Density of the Catalysts?

2008· article· en· W2006953628 on OpenAlexfundno aff
Juan Herranz, Michel Lefèvre, Jean‐Pol Dodelet

Bibliographic record

VenueECS Transactions · 2008
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersGeneral Motors of Canada
KeywordsAdsorptionMicroporous materialPoint of zero chargeCatalysisInorganic chemistryCarbon fibersChemistryMetalOxygenNoble metalNitrogenMaterials sciencePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The adsorption of iron II acetate over two microporous carbon blacks of different surface properties was studied in order to determine if this factor limits the activity of Fe/N/C catalysts for ORR made with these carbon supports. Whereas one of these carbons only had oxygen-derived functionalities over its surface, the other one contained both oxygen and nitrogen bearing functionalities. Their points of zero charge (PZC) were first determined to be 3.9 and 8.8, respectively. Adsorption curves showing the evolution of the metallic uptake with the pH revealed that both carbon supports are able to adsorb 100% of the positive Fe ions in solution at pH>4, and this up to 0.8 wt% Fe. Therefore, the adsorption of iron is not the factor responsible for the limited site density of Fe/N/C catalysts having a Fe content {less than or equal to} 0.8 wt% loaded either by adsorption or by wet-impregnation of the carbon supports.

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)0.001
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 score0.077
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.200
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 teacher head, 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

Citations0
Published2008
Admission routes1
Has abstractyes

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