MétaCan
Menu
Back to cohort
Record W2185621319 · doi:10.14447/jnmes.v14i2.112

Kinetic Study of Oxygen Reduction Reaction on Palladium Nanoparticles Supported in Thermally Treated Carbon

2011· article· en· W2185621319 on OpenAlexvenueno aff
R. Huerta, Publio Puente, Omar Solorza Feria

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2011
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsnot available
Fundersnot available
KeywordsPalladiumRotating disk electrodeElectrocatalystElectrochemistryRaman spectroscopyCarbon fibersRotating ring-disk electrodeHydrogen peroxideChemistryOxygenScanning electron microscopeElectrodeNanoparticleNuclear chemistryHydrogenCatalysisInorganic chemistryMaterials scienceNanotechnologyPhysical chemistryCyclic voltammetryComposite numberOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The kinetic study of oxygen reduction reaction (ORR) using palladium nanoparticles supported in thermally-treated Vulcan® carbon as an electrocatalyst was developed in a 0.5 M H2SO4 solution. The Vulcan® carbon was thermally treated at 400oC and 600°C. The Pd supported in thermally treated carbon (Pd/TTC) was synthesized by PdCl2 reduction with NaBH4 in water at 60°C. The thermally treated carbon (TTC) was evaluated by Raman spectroscopy, whereas the morphology of Pd/TTC was characterized by Scanning Electron Microscopy (SEM). The electrochemical activity was studied by rotating disk electrode (RDE) and rotating ring-disk electrode (RRDE) techniques. The RDE result showed a high activity of the Pd/TTC towards the ORR, this reaction proceeds preferentially via a 4e- pathway. On the other hand, the hydrogen peroxide productions were 4.6% and 6.6% for Pd/(TTC at 400°C) and 600°C, respectively.

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)0.0010.000

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 head0.022
GPT teacher head0.235
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

Citations1
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of New Materials for Electrochemical SystemsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207