Programmable Circularly Polarized Electroluminescence Through Stereocontrol of Chiral Liquid‐Crystalline Co‐Assemblies
Bibliographic record
Abstract
Abstract Circularly polarized organic light‐emitting diodes (CP‐OLEDs) are essential to prospective 3D displays and advanced polarized lighting systems. The rational design of programmable circularly polarized electroluminescence (CP‐EL) materials with a large electroluminescence dissymmetry factor (gEL) remains a great challenge and is still in its preliminary exploration phase. In this work, two aggregation induced emission active (AIE‐active) chiral inducers with different dihedral angles of binaphthalene (S‐/R‐1 and S‐/R‐2) and achiral acrylate‐based liquid crystalline polymer (LCP) (PyP) were chosed to construct chiral co‐assemblies through an intermolecular chirality induction mechanism. Interestingly, as the dihedral angle of the AIE‐active binaphthyl inducer decreased from obtuse to acute angle, the resulting co‐assemblies (S‐/R‐2‐PyP) could emit inverted and amplified CP‐EL signals compared with S‐/R‐1‐PyP after annealing. Significantly, the (S‐/R‐2)0.1‐(PyP)0.9‐based CP‐OLEDs displayed remarkable blue CP‐EL (λEL = 480 nm, Lmax = 14860 cd m−2) with a record |gEL| value of up to 0.18 in chiral co‐assembled CP‐OLEDs to date. This work describes the first observation of dynamic CP‐EL with tunable signal direction and intensity through stereocontrol of AIE‐active chiral inducers in LCP co‐assembled films, providing a valuable guidance for realizing programmable CP‐EL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".