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Record W2076235405 · doi:10.1021/la010415d

Formation of Multilayers on Glassy Carbon Electrodes via the Reduction of Diazonium Salts

2001· article· en· W2076235405 on OpenAlexafffund
James K. Kariuki, Mark T. McDermott

Bibliographic record

VenueLangmuir · 2001
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlassy carbonElectrochemistryElectrodeDiazonium CompoundsElectrolysisCarbon fibersDeposition (geology)Materials scienceSalt (chemistry)GraphiteChemical engineeringThin filmRedoxChemistryInorganic chemistryNanotechnologyCyclic voltammetryOrganic chemistryComposite numberPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

The functionalization of carbon electrodes with aryl films can be achieved via the electrochemical reduction of the corresponding diazonium salt. We have previously shown that this deposition procedure will produce multilayer films on ordered graphite under certain conditions. We examine here the formation of multilayer films on glassy carbon (GC) electrodes by potential step electrolysis of diazonium salts for longer periods of time. The deposition of diethylaniline (DEA) is tracked with the use of infrared reflectance absorption spectroscopy and scanning force microscopy. DEA is continually deposited over a 30 min potential step and the film thickness approaches 20 nm. Phenylacetic acid and nitrophenyl films that are 15−25 nm thick can also be deposited in this way. We also find that, despite the presence of a relatively thick DEA film on a GC electrode, electron transfer to benchmark redox systems is not completely blocked. We attribute the compromised blocking to a high density of defects in the film structure.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations318
Published2001
Admission routes2
Has abstractyes

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