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Record W2121658228 · doi:10.1115/1.4031385

Flexible Cellulose-Based Films of Polyaniline–Graphene–Silver Nanowire for High-Performance Supercapacitors

2015· article· en· W2121658228 on OpenAlexafffund
Ali Khosrozadeh, Mohammad Ali Darabi, Malcolm Xing, Quan Wang

Bibliographic record

VenueJournal of Nanotechnology in Engineering and Medicine · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolyanilineSupercapacitorGrapheneCapacitanceCelluloseComposite numberFabricationTernary operationChemical engineeringNanotechnologyComposite materialPolymerElectrode

Abstract

fetched live from OpenAlex

We report a facile fabrication of a high-performance supercapacitor (SC) using a flexible cellulose-based composite film of polyaniline (PANI), reduced graphene oxide (RGO), and silver nanowires (AgNWs). The flexibility, high capacitive behavior, cyclic stability, and enhanced rate capability of the entire device make it a good candidate for flexible and wearable SCs. Our results demonstrate that a capacitance as high as 73.4 F/g (1.6 F/cm2) at a discharge rate of 1.1 A/g is achieved. In addition, the SC shows a power density up to 468.8 W/kg and an energy density up to 5.1 Wh/kg. The flexibility of the composite film is owing to the binding effect of cellulose fibers as well as AgNWs. The superb electrochemical performance of the device is found to be mainly attributed to the synergistic effect between PANI/RGO/AgNWs ternary in a cushiony cellulose scaffold and porous structure of the composite.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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

Citations14
Published2015
Admission routes2
Has abstractyes

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