Recent Advances in Circularly Polarized Luminescence of Liquid Crystalline Aggregation‐Induced Emission Materials
Bibliographic record
Abstract
Abstract Circularly polarized luminescence (CPL) materials have gained increasing attention for their potential in advanced photonic and chiroptical technologies. Among them, AIE‐CPL‐LC materials integrating aggregation‐induced emission (AIE) with liquid crystalline (LC) order represent a distinctive class of CPL materials. These materials not only exhibit strong emission in the condensed phase but also demonstrate efficient chirality transfer and a remarkable amplification effect of chiral signals. This review summarizes recent advances in the design, assembly, and functional modulation of AIE‐CPL‐LC materials. A key feature is the significant enhancement of luminescence dissymmetry factor ( g lum ) achieved by the self‐assembled ordering of mesogens while maintaining strong AIE performance. This enhancement arises from the chiral amplification effect driven by the ordered mesogenic structures, which extend chiral organization from the nanoscale to mesoscopic or even macroscopic levels through helical superstructures. Such hierarchical chirality amplification enhances g lum by orders of magnitude, thereby improving the CPL efficiency. The intrinsic asymmetry of chiral mesogenic structures may also contribute to CPL activity. Special emphasis is placed on elucidating structure‐property relationships, particularly the influence of mesophase type, molecular alignment, and external stimuli on g lum and the photoluminescence quantum yield. AIE‐CPL‐LC materials offer a versatile and powerful foundation for the next‐generation chiral photonic devices development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".