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Record W2284386973 · doi:10.14447/jnmes.v16i3.17

The Effect of Binder in Electrode Materials for Capacitance Improvement and EDLC Binder-free Cell Design

2013· article· en· W2284386973 on OpenAlexvenueno aff
R. López-Chavéz, Ana Karina Cuentas-Gallegos

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2013
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceElectrodePolyvinylidene fluorideSupercapacitorCapacitanceCyclic voltammetryCurrent collectorComposite materialCarbon fibersElectrochemistryComposite numberChemistryPolymer

Abstract

fetched live from OpenAlex

In the present work we show results related with the influence of the binder type used to elaborate active electrodes made of activated carbon (DLC) for the assembly of supercapacitor cells. A Nafion 5%w solution and/or Kinar Flex (Polyvinylidene fluoride, PVDF) were used as binders at different concentrations, using DLC carbon as the active material to make the electrodes by aerography, and carbon paper as support and current collector. Thickness of the electrodes was controlled by the weight of active material (DLC carbon). Cyclic voltammetry technique was used to investigate the intrinsic capacitive nature of these electrodes, increasing this value from 120 F/g to 245 F/g at 20 mV/s just by improving the type and amount of binder, and the thickness of the electrode. Symmetric 2-electrode cells assembled with binder-free electrodes were electrochemically characterized by galvanostatic cycling, showing capacitance values of 38F/g and a stable behavior during 7000 charge-discharge cycles.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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 teacher head, 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

Citations16
Published2013
Admission routes1
Has abstractyes

Explore more

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