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Auroralike Light from a Polymer <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mrow> <mml:mi>p</mml:mi> </mml:mrow> <mml:mtext>−</mml:mtext> <mml:mrow> <mml:mi>n</mml:mi> </mml:mrow> </mml:mrow> </mml:math> Junction Emitting Free Electrons

2025· article· lv· W4408226612 on OpenAlexafffund
Dongze Wang, Jun Gao

Bibliographic record

VenuePhysical Review Letters · 2025
Typearticle
Languagelv
FieldEngineering
TopicNonlinear Optical Materials Studies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer sciencePhysics

Abstract

fetched live from OpenAlex

Luminescent conjugated polymers are organic semiconductors possessing unique electrical and optical properties. Luminescent polymers have been extensively investigated because of their potential applications in light sources and display devices. Here, we provide the first evidence that a luminescent polymer is also a strong emitter of free electrons and a source of new light. Vivid green light flashes have been observed from a red-emitting polymer p-n junction under a large reverse bias. The p-n junctions have a planar configuration, revealing that the green light flashes are emitted into free space, far beyond the confines of electrodes. Moreover, the green flashes can be strongly distorted by a permanent magnet placed nearby, generating a light show resembling an aurora. Like the aurora, the green light flashes are caused by charged particles. By applying a known transverse magnetic field to bend the flashes into circular arcs, a charge to mass ratio is determined for the charged particles. The auroralike green light coincides with the formation of electrical trees in the n-doped region of the junction. We postulate that the green light is caused by field-emitted electrons exciting an unknown organic vapor released in the treeing process.

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 score0.002
Threshold uncertainty score0.008

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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