Quantum Dot/Liquid Crystal Nanocomposites in Photonic Devices
Bibliographic record
Abstract
Quantum dot/liquid crystal nano-composites are promising new materials for a variety of applications in energy harvesting, displays and photonics including the liquid crystal laser. To realize many applications, however, we need to control and stabilize nano-particle dispersion in different liquid crystal host phases and understand how the particles behave in an anisotropic fluid. An ideal system will allow for the controlled assembly of either well-defined nano-particle clusters or a uniform particle distribution. In this paper, we investigate mesogen-functionalized quantum dots for dispersion in cholesteric liquid crystal. These nanoparticles are known to assemble into dense stable packings in the nematic phase, and such structures, when localized in the liquid crystal defects, can potentially enhance the coupling between particles and a cholesteric cavity. Controlling the dispersion and assembly of quantum dots using mesogenic surface ligands, we demonstrate how resonant fluid photonic cavities can result from the co-assembly of luminescent nanoparticles in the presence of cholesteric liquid crystalline ordering.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".