Thermo-, photo-, and mechano-responsive liquid crystal networks enable tunable photonic crystals
Bibliographic record
Abstract
Tunable photonic crystals exhibiting optical properties that respond reversibly to external stimuli have been developed using liquid crystal networks (LCNs) and liquid crystal elastomers (LCEs). These tunable photonic crystals possess an inverse opal structure and are photo-responsive, but circumvent the usual requirement to contain dye molecules in the structure that often limit their applicability and cause optical degradation. Herein, we report tunable photonic crystal films that reversibly tune the reflection peak wavelength under thermo-, photo- and mechano-stimuli, through bilayering a stimuli-responsive LCN including azobenzene units with a colourless inverse opal film composed of non-responsive, flexible durable polymers. By mechanically deforming the azobenzene containing LCN via various stimuli, the reflection peak wavelength from the bilayered film assembly could be shifted on demand. We confirm that the reflection peak shift occurs due to the deformation of the stimuli-responsive layer propagating towards and into the inverse opal layer to change its shape in response, and this shift behaviour is repeatable without optical degradation.
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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".