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Record W2760332195 · doi:10.1134/s1023193517090117

Electrochemical oxidation of formic acid at carbon supported Pt coated rotating disk electrodes

2017· article· en· W2760332195 on OpenAlexafffund
Azam Sayadi, Peter G. Pickup

Bibliographic record

VenueRussian Journal of Electrochemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChronoamperometryCyclic voltammetryChemistryRotating disk electrodeFormic acidGlassy carbonElectrochemistryAnalytical Chemistry (journal)DiffusionElectrocatalystVoltammetryInorganic chemistryElectrodeReaction rate constantThermodynamicsKineticsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The effect of electrode rotation on the oxidation of formic acid in aqueous sulphuric acid has been investigated at a glassy carbon electrode coated with a carbon supported Pt catalyst. Substantial mass transport effects were observed in cyclic voltammetry, steady-state measurements at constant potential, and chronoamperometry. However, a purely mass transport limited current was not observed under any conditions because of a decrease in the kinetic current at high potentials due to Pt oxide formation. Steady-state measurements, and currents from the cathodic scans in cyclic voltammetry, gave linear Koutecky–Levich plots with slopes in agreement with the literature diffusion coefficient. However, non-linearity and inaccurate slopes were observed for anodic scans and chronoamperometry. This has been shown to be due to small increases in the kinetic current with increasing rotation rate. Accurate kinetic currents can be obtained by applying the Koutecky–Levich equation at each rotation rate and use of the known mass transport limited current.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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