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Record W2783576793 · doi:10.14447/jnmes.v17i2.434

Impedance Analysis of Growth and Morphology of Electropolymerized Polypyrrole Nanocomposites

2014· article· en· W2783576793 on OpenAlexvenueno aff
Morteza Torabi, Maryam Dehghani Soltani, S.K. Sadrnezhaad

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2014
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsnot available
Fundersnot available
KeywordsPolypyrroleNanocompositeMorphology (biology)Materials scienceScanning electron microscopeElectrical impedanceDeposition (geology)ElectrochemistryPolymerizationChemical engineeringComposite materialDielectric spectroscopyPolymerChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Pure polypyrrole (PPy), PPy/Al2O3 and PPy/SiO2 nanocomposites synthesized galvanostatically using different polymerization charges. Electrochemical impedance measurements of pure polypyrrole revealed that the film thickness affected the impedance responses. The characteristic frequencies vs. film thickness that obtained using Cole-Cole plots showed that electrodeposition mechanism changed from 3D to 1D after nuclei overlapping for pure PPy. Analysis of the nanocomposites impedance spectrums revealed no changes during the film growth, i.e. deposition continues 3D even after nuclei overlapping. Scanning electron microscopy (SEM) confirmed the impedance results and showed that the morphology of the thick pure PPy film is 1D, while the deposition of the nanocomposites was 3D with compact and very fine 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 score0.004

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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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