Inside Front Cover: Unprecedented Dual Alignment Mode and Freedericksz Transition in Planar Nematic Liquid Crystal Cells Doped with Gold Nanoclusters (Adv. Funct. Mater. 2/2008)
Bibliographic record
Abstract
Abstract On p. 212, Torsten Hegmann and co‐workers describe nematic liquid crystals (N‐LCs) confined in planar liquid crystal cells after doping with small quantities of gold nanoclusters. These give rise to a dual alignment mode and electro‐optic response (Freedericksz transition). By fine‐tuning of experimental conditions, N‐LCs doped with gold nanoclusters can be electrically reoriented and aligned either like N‐LCs with a positive dielectric anisotropy (used in twisted nematic displays) in a planar cell or alternatively as N‐LCs with a negative dielectric anisotropy (used in large LCD TVs based on the vertical alignment mode). We demonstrate that alkylthiol‐capped gold nanoclusters doped into nematic liquid crystals (N‐LCs) with positive dielectric anisotropy give rise to an unprecedented dual alignment mode and electro‐optical response, which has a potential impact on current liquid crystal (LC) display technologies and N‐LC optical‐biosensor design. By fine‐tuning experimental conditions (temperature, electric field, and alignment), N‐LCs doped with gold nanoclusters can be aligned and electrically reoriented either like N‐LCs with a positive dielectric anisotropy in a planar cell or, alternatively, as N‐LCs with a negative dielectric anisotropy in a homeotropic cell, both at lower threshold voltages than the pure N‐LC.
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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) | 0.013 | 0.003 |
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".