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Record W2090838715 · doi:10.1021/jp021634q

Oxygen Reduction Catalysts for Polymer Electrolyte Fuel Cells from the Pyrolysis of Iron Acetate Adsorbed on Various Carbon Supports

2003· article· en· W2090838715 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2003
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaStiftelsen för Miljöstrategisk Forskning
KeywordsCarbon blackCatalysisCarbon fibersPyrolysisElectrocatalystChemistryElectrolyteAdsorptionElectrochemistryOxygenInorganic chemistryCarbonizationChemical engineeringMaterials scienceOrganic chemistryElectrodeComposite number

Abstract

fetched live from OpenAlex

Nonnoble metal catalysts for the electrochemical reduction of oxygen in acidic medium have been produced by adsorbing iron(II) acetate on 19 carbon supports. These materials were then pyrolyzed in an atmosphere containing NH 3 . The 19 carbon supports are (i) six as-received commercial supports (Printex XE-2, Norit SX Ultra, Ketjenblack EC-600JD, acetylene black, Vulcan XC-72R, and Black Pearls 2000), (ii) three as-received developmental supports (Lonza HS300 and Sid Richardson RC1 and RC2), (iii) the same nine previous supports prepyrolyzed at 900 °C in an atmosphere containing NH 3 to increase their N content, and (iv) a synthetic carbon made by pyrolyzing perylene tetracarboxylic dianhydride at 900 °C in an atmosphere containing NH 3. The goal of this study is to determine the effect of the carbon support on the catalytic activity of the catalysts. The specific surface area, the pore size distribution, the N and O contents, and the electrocatalytic activities of the 19 types of catalysts were measured. It was found that the activity of the catalysts varies greatly from one carbon support to another, but neither the specific surface area of the catalysts nor the distribution of their macro- or mesopores is a determining factor for the catalytic activity. The most important factor is the N content of the materials; the higher it is, the higher is the density of the catalytic sites on their surface and the better is the electrocatalyst. Carbon supports that are devoid of N, however, display some lower catalytic activity, which is attributed to an iron oxide. The latter catalytic site occurs also in the other N-containing catalysts. In these materials there are, therefore, three catalytic sites at work: an iron oxide site and two N-containing sites labeled FeN 4 /C and FeN 2 /C, with the last site being the most active for oxygen electroreduction.

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 score0.014
Threshold uncertainty score0.371

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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