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Record W4385487015 · doi:10.1002/admt.202300824

Extremely Large Polymer Light‐Emitting Electrochemical Cells with Concentric Circular Electrodes

2023· article· en· W4385487015 on OpenAlexafffund
Abhishake Goyal, Dongze Wang, Jun Gao

Bibliographic record

VenueAdvanced Materials Technologies · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrodeMaterials scienceRADIUSConcentricOptoelectronicsDopingOpticsAuxiliary electrodeElectrolyteChemistryGeometryPhysics

Abstract

fetched live from OpenAlex

Abstract Planar polymer light‐emitting electrochemical cells (LECs) with concentric circle electrodes are demonstrated. With a fixed outer electrode radius of 6.8 mm, the inner electrode radius is varied from 1 to 3 mm. All cells can be activated with a 40 V bias at 360 K. The extremely large electrode gap size allows for time‐lapsed imaging of the in situ electrochemical p‐ and n‐doping processes. When the advancing p‐ and n‐doping fronts meet, a light‐emitting junction in the shape of a jagged ring is formed near the center of the electrode gap. Reversing bias polarity pushes the light‐emitting junction outward to near the negative electrode. It is possible to achieve a perfectly centered emitting junction by fine tuning the inner electrode radius. The sensitivity of junction position to relative electrode radius indicates the p‐ and n‐doping reactions are strongly coupled. The concentric circular electrode configuration offers a cross sectional view of an LEC‐based light‐emitting fiber. In any fiber shaped light‐emitting device, the inner and outer electrodes always differ in size. This electrode asymmetry should be considered and exploited to achieve optimal cell performance.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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