Optical behaviour of hybrid LC/inorganic nanostructures
Bibliographic record
Abstract
Porous thin films of dielectric materials have been deposited using e-beam evaporation onto substrates held at highly oblique angles (> 80o), coupled with simultaneous computer controlled substrate motion about two independent axes. This technique, known as glancing angle deposition (GLAD), enables the formation of shaped, isolated nanostructures, including vertical posts, zig-zags, and both helical and polygonal spirals, which exhibit chiral optical properties. GLAD films form the backbone of liquid crystal (LC) hybrid optical materials and devices, and afford key advantages. The porous nature of the GLAD structures allows LCs to uniformly penetrate the film and modify its optical properties. Addition of LCs to GLAD films improves the properties of the films by reducing optical scattering, enhancing transmission, and accentuating existing chiral and linear optical anisotropies. Further, by mixing a dichroic dye with the LCs, polarization selective optical properties can be introduced into the film which can be used to augment the functionality of GLAD films. It has been found that addressing hybrid GLAD films with an electric field reorients the LCs, allowing one to switch the optical properties of the composite film. This behaviour extends to LCs mixed with dichroic dye, allowing one to switch the selective polarization properties with an applied voltage. Using results based on spectroscopic ellipsometry, we will examine the optical properties and switching behaviour of LC/dichroic dye hybrid GLAD films and discuss how the results allow one to infer the alignment of LCs in GLAD films, as well how the addition of dichroism to the film affects the selective transmission of both linearly and circularly polarized light.
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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".