Nanocomposites of a nematic liquid crystal doped with magic-sized CdSe quantum dots
Bibliographic record
Abstract
We here report on the optical, alignment and electro-optic properties of a nematic liquid crystal affected by the presence of semiconductor CdSe magic-sized nanocrystals (MSNCs). Three single-sized CdSe samples were tested, exhibiting bright bandgap photoluminescence (PL) with λmax ≈ 463 nm and ∼10 nm full width at half-maximum (fwhm). The three quantum dot (QD) samples were passivated with a monolayer of myristic acid. Two of them (QD1 and QD2) only vary in the amount of defects as indicated by different bandgap and deep trap PL. The third MSNC sample (QD3) is compositionally different, doped with Zn. These MSNCs with almost identical sizes were doped at different concentrations (1–5 wt%) into the nematic phase of 5-n-heptyl-2-(4-n-octyloxyphenyl)-pyrimidine (LC1). Only QD3 showed the formation of birefringent stripes surrounded by areas of homeotropic alignment between plain glass slides at all concentrations as observed for many other nanoparticle-doped nematic liquid crystals reported earlier by our group. In polyimide-coated glass slides favouring planar orientation of the nematic director, planar alignment was observed. Surprisingly, only the Zn-doped magic-sized QD3quantum dots (CdSe@Zn) significantly lower the dielectric anisotropy as well as the splay elastic constant of the nematic host, despite identical size and surface functionality, which highlights the tremendous effect of the nanocrystal core composition on the electro-optic properties of the nematic host. In addition, fluorescence confocal (polarizing) microscopy studies show the director field within and around the birefringent stripes and confirm locally elevated concentrations or aggregates of the MCNC that are otherwise randomly distributed in the nematic host.
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 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".