Bibliographic record
Abstract
The classic challenge faced by researchers dealing with liquid crystals is to control the LC molecular orientation and hence optimise the optical properties. Well known techniques for influencing LC texture include the use of surfactants or thin film alignment layers. The underlying limitation common to such techniques is that while excellent control of LC anchoring at the substrate surface is achieved, molecular alignment in the bulk of the LC is reliant entirely upon the cooperative effects and resulting elastic properties of the LC material. Generally, this has worked sufficiently well in practice, but unfortunately, the complete dependence on the intermolecular forces of the LC means that unencumbered, reversible switching is not always possible. Our group has taken a unique approach to influence LC orientation. Using glancing angle deposition (GLAD), highly porous thin films can be grown possessing isolated columnar microstructure whose shape can be tailored via substrate motion during film deposition. In particular, we can grow films of helical columns with controlled pitch and handedness. These films exhibit circular dichroism and optical activity similar to that seen in chiral LCs. The high porosity of GLAD films permits fluids such as LCs to be introduced into the pores, leading to a new type of hybrid optical material. Most significantly, initial work showed that when achiral LCs were embedded in chiral GLAD media, there was an enhancement of the circular dichroism and optical activity as the chiral GLAD film served to induce a chiral orientation in the LC. In this report, we start with a brief overview of the GLAD process and some relevant optical studies, leading to a review of GLAD/LC hybrid materials, switchable devices, and finally, a discussion of recent research optical characterisation and some ideas for future avenues of investigation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".