Hydrophobic gold nanoparticles via silane conjugation: chemically and thermally robust nanoparticles as dopants for nematic liquid crystals
Bibliographic record
Abstract
We examine for the first time how chemically and thermally stable gold nanoparticles (NPs), prepared by a silane conjugation approach, affect both the thermal and the electro-optical properties of a nematic liquid crystal (LC), when doped at concentrations ranging from 0.25 to 7.5 wt%. We find that the octadecylsilane-conjugated gold NPs stabilize both the enantiotropic nematic and the monotropic smectic-A phases of the LC host with a maximum stabilization of 2(°)C for the nematic and 3.5(°)C for the smectic-A phases for the mixture containing 1 wt% of the silanized particles. The same mixture shows the lowest values for the Fréedericksz transition threshold voltage and the highest value for the dielectric anisotropy. Generally, all NP-containing mixtures, except mixtures with NP concentrations exceeding 5 wt%, reduce the threshold voltage, increase the dielectric anisotropy and reduce both rise and decay time; the latter particularly at temperatures at least 10(°)C below the isotropic-nematic phase transition on cooling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".