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Record W2583004931 · doi:10.1002/admt.201600282

Highly Stretchable Micro‐Supercapacitor Arrays with Hybrid MWCNT/PANI Electrodes

2017· article· en· W2583004931 on OpenAlexaff
La Li, Zheng Lou, Wei Han, Di Chen, Kai Jiang, Guozhen Shen

Bibliographic record

VenueAdvanced Materials Technologies · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsSupercapacitorMaterials scienceStretchable electronicsCapacitanceElectrodeOptoelectronicsNanotechnologyPolyanilineCarbon nanotubePower densityEnergy storageWearable technologyElectronicsWearable computerComposite materialElectrical engineeringPower (physics)PolymerComputer science

Abstract

fetched live from OpenAlex

Stretchable energy storage devices are required to fit for stretchable electronic devices, forming a fully stretchable system for comfortable and body‐attachable electronic devices. Herein, highly stretchable micro‐supercapacitors are fabricated by designing wave‐shaped hybrid multiwalled carbon nanotubes/polyaniline electrodes. As‐fabricated stretchable devices exhibit a large areal capacitance of 44.13 mF cm−2 and offer a power density of 0.07 mW cm−2 at an area energy density of 0.004 mW h cm−2. Owing to the designed wavy electrode structure, the electrochemical performances of the stretchable micro‐supercapacitors are almost invariably under different stretching stations ranging from 5% to 40%. By fabricating stretchable micro‐supercapacitors arrays, a red light‐emitting diode can be easily lighted under different conditions including stretching, twisting, crimping, and winding. All these results confirm the outstanding stability and mechanical strength of stretchable micro‐supercapacitors, demonstrating its potential application in skin‐patchable electronics or portable/wearable devices.

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 score0.003

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 communication0.0000.001
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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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

Citations178
Published2017
Admission routes1
Has abstractyes

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