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Record W2016712210 · doi:10.1007/s11671-009-9519-z

Electrodeposition and Capacitive Behavior of Films for Electrodes of Electrochemical Supercapacitors

2010· article· en· W2016712210 on OpenAlexafffund
Cai Shi, Igor Zhitomirsky

Bibliographic record

VenueNanoscale Research Letters · 2010
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanochemistrySupercapacitorMaterials scienceCapacitive sensingElectrochemistryElectrodeNanotechnologyOptoelectronicsChemical engineeringElectrical engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Polypyrrole films were deposited by anodic electropolymerization on stainless steel substrates from aqueous pyrrole solutions containing sodium salicylate and tiron additives. The deposition yield was studied under galvanostatic conditions. The amount of the deposited material was varied by the variation of deposition time at a constant current density. SEM studies showed the formation of porous films with thicknesses in the range of 0-3 μm. Cyclic voltammetry data for the films tested in 0.5 M Na2SO4 solutions showed capacitive behavior and high specific capacitance (SC) in a voltage window of 0.9 V. The films prepared from pyrrole solutions containing tiron showed better capacitive behavior compared to the films prepared from the solutions containing sodium salicylate. A highest SC of 254 F g-1 was observed for the sample with a specific mass of 89 μg cm-2 at a scan rate of 2 mV s-1. The SC decreased with an increasing film thickness and scan rate. The results indicated that the polypyrrole films deposited on the stainless steel substrates by anodic electropolymerization can be used as electrodes for electrochemical supercapacitors (ES).

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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

Citations60
Published2010
Admission routes2
Has abstractyes

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