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Record W2695775421 · doi:10.14447/jnmes.v13i4.139

Electrochemical Behavior Of Resorcinol at a Gold Nanoparticle/Carbon Nanotube Composite Modified Glassy Carbon Electrode

2010· article· en· W2695775421 on OpenAlexvenueno aff
Yongping Dong

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
Fundersnot available
KeywordsResorcinolElectrodeElectrochemistryCarbon nanotubeMaterials scienceColloidal goldGlassy carbonChemically modified electrodeNanotubeInorganic chemistryNanoparticleChemical engineeringWorking electrodeCyclic voltammetryNanotechnologyChemistryOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A Gold nanoparticle/carbon nanotube composite modified glassy carbon electrode was fabricated by simple casting method and was used to study the electrochemical behavior of resorcinol in neutral pH condition. The modified electrode exhibited synergistic electrochemical catalytic effects of carbon nanotube and gold nanoparticles on the electrochemical reactions of resorcinol. The intensity of oxidation peak of resorcinol on the modified electrode was enhanced about 10-times compared with that on the bare electrode. The electrochemical reaction was mainly controlled by diffusion process. The layers of composite, pH, electrolytes could influence electrochemical signal of resorcinol. The stability and reproducibility of the modified electrode is good. The oxidation peak current was proportional to resorcinol concentration in the range of 1 x 10(-5) to 1 x 10(-3) mol/L and the detection limit of resorcinol was 5.0 x 10(-6) mol/L, demonstrating that it is promising for the detection of resorcinol using the gold nanoparticle/carbon nanotube modified glassy carbon electrode.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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