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Record W4412110947 · doi:10.1002/anie.202512257

Chiral Co‐Assembled Liquid Crystal Polymer Network Enabled by In‐Situ Photopolymerization for High‐Performance CP‐OLEDs

2025· article· en· W4412110947 on OpenAlexaff
Chunya Fu, Dong Li, Chao Liu, Yu Zhang, Jun‐Sheng Zhang, Yixiang Cheng

Bibliographic record

VenueAngewandte Chemie International Edition · 2025
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsMaterials sciencePhotopolymerOLEDLiquid crystalMonomerPolymerElectroluminescenceFabricationOptoelectronicsDiodeCholesteric liquid crystalNanotechnologyLayer (electronics)Composite material

Abstract

fetched live from OpenAlex

Abstract Circularly polarized organic light‐emitting diodes (CP‐OLEDs) show great promise for next‐generation display technologies. However, achieving high dissymmetry factors (| g EL |) in circularly polarized electroluminescence (CP‐EL) remains a significant challenge. In this study, we construct a novel chiral co‐assembled cholesteric liquid crystal polymer network ( ChLC‐PN ) as an emitting layer (EML) to enhance CP‐EL via a facile in situ photopolymerization strategy. The ChLC‐PN was fabricated by UV‐induced polymerization (365 nm, 200 mW cm − 2 , 2 min, N₂ atmosphere) of a chiral co‐assembly system comprising liquid crystal monomer ( LCM ) and chiral inducers ( R / S ‐Cz ). Notably, the resulting ( R / S ‐Cz) 0.01 ‐(LCP) 0.99 based devices demonstrate sky‐blue CP‐EL with a maximum | g EL | value of 0.012. This work presents the first report of high‐performance CP‐OLEDs utilizing a chiral co‐assembled cholesteric liquid crystal rigid polymer network, offering a promising platform for simple, stable, and scalable fabrication of future CP‐OLED 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 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)0.000
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 score0.037
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

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 head0.010
GPT teacher head0.285
Teacher spread0.275 · 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

Citations18
Published2025
Admission routes1
Has abstractyes

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