Synthesis of Liquid Crystal Silane‐Functionalized Gold Nanoparticles and Their Effects on the Optical and Electro‐Optic Properties of a Structurally Related Nematic Liquid Crystal
Bibliographic record
Abstract
Chemically and thermally robust liquid crystal silane-functionalized gold nanoparticles (i.e. AuNP1-AuNP3) were synthesized through silane conjugation. Colloidal dispersions of these particles with mesogenic ligands that are structurally identical (as in AuNP1, AuNP2) or compatible (as in AuNP3) with molecules of the nematic liquid crystal (N-LC) host showed superior colloidal stability and dispersibility. The thermal, optical, and electro-optic behaviors of the N-LC composites at different concentrations of each gold nanoparticle were investigated. All dispersions showed lower values for the rotational viscosity and elastic constant, but only AuNP3 with a dissimilar structure between the nanoparticle ligand and the host displayed the most drastic thermal effects and overall strongest impact on the electro-optic properties of the host. The observed results were explained considering both the structure and the density of the surface ligands of each gold nanoparticle.
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) | 0.000 | 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 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".