Bibliographic record
Abstract
Nanoparticles (NPs) have emerged as extremely promising materials to alter and improve the properties of liquid crystals (LCs) used, for example, in device applications. In this paper, we summarise recent work from our lab that aims to provide a fundamental understanding of structure–property and composition–property relationships governing LC–NP interactions, which may point to new directions for major improvements in the efficiency of LCs used in display applications. A variety of LC hosts (phases) doped with surface-functionalised gold NPs have been systematically studied ranging from one-dimensionally ordered nematic over two-dimensionally ordered smectic to three-dimensionally ordered columnar phases. Significant progress with respect to LC–NP interactions was made for NP-doped nematic phases. Here, the observation of an unusual texture for Au NP-doped nematic LCs, that is, the formation of birefringent stripe textures and the induction of homeotropic alignment of the nematic LC similar to chiral finger (or fingerprint) textures, provided the basis for numerous experimental studies using Au NPs with different core sizes and surface functionalities.
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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) | 0.003 | 0.001 |
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".