Miscibility and Alignment Effects of Mixed Monolayer Cyanobiphenyl Liquid‐Crystal‐Capped Gold Nanoparticles in Nematic Cyanobiphenyl Liquid Crystal Hosts
Bibliographic record
Abstract
Against the rule: Liquid crystal hosts (5CB and 8CB) are doped with different thiol decorated gold nanoparticles (see figure). The "simple" hexanethiol and dodecanethiol capped nanoparticles (Au1 and Au2) are more compatible to the nematic cyanobiphenyl liquid crystals than nanoparticles capped simultaneously with alkylthiols and a nematic cyanobiphenyl thiol (Au3 and Au4).This study focuses on the miscibility of liquid crystal (LC) decorated gold nanoparticles (NPs) in nematic LCs. To explore if LC functional groups on the gold NP corona improve the compatibility (miscibility) with structurally related LC hosts, we examined mixtures of two LC hosts, 5CB and 8CB, doped at 5 wt % with different types of gold NPs. Four alkanethiol-capped NPs were synthesized; two homogeneously coated with alkanethiols (Au1 with C(6)H(13)SH and Au2 with C(12)H(25)SH), and two that were additionally capped at a different ratio with a mesogenic cyanobiphenyl end-functionalized alkanethiol HS10OCB (C(6)H(13)SH + HS10OCB for Au3 and C(12)H(25)SH + HS10OCB for Au4). Investigating these mixtures in the bulk for settling of the NPs, and in thin films using polarized optical microscopy (POM) between untreated glass slides as well as POM studies and electro-optic tests in planar ITO/polyimide test cells, reveal that the alkanethiol capped NPs Au1 and Au2 are more compatible with the two polar cyanobiphenyl hosts in comparison to the NPs decorated with the cyanobiphenyl moieties. All NPs induce homeotropic alignment in 5CB and 8CB between untreated glass slides, with Au1 and Au2 showing characteristic birefringent stripes, and Au3 and A4 exhibiting clear signs of aggregation. In rubbed polyimide cells, however, Au3 and Au4 fail to induce homeotropic alignment and show clear signs of macroscopic aggregation.
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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) | 0.001 | 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".