Cellulose Nanocrystal Elastomers with Reversible Visible Color
Bibliographic record
Abstract
Responsive photonic crystals have potential applications in mechanical sensors and soft displays; however, new materials are constantly desired to provide new innovations and improve on existing technologies. To address this, we report stretchable chiral nematic cellulose nanocrystal (CNC) elastomer composites that exhibit reversible visible color upon the application of mechanical stress. When stretched (or compressed) the colorless materials maintain their chiral nematic structure but the helical pitch is reduced into the visible region, resulting in coloration of the CNC-elastomer composite. By increasing the percentage elongation of the material (ca. 50-300 %), the structural color can be tuned from red to blue. The color of the materials was characterized by reflectance optical microscopy and reflectance circular dichroism to confirm the wavelength and polarization of the reflected light. We also probed the mechanism of the structural color using 2D-X-ray diffraction. Finally, by either water-patterning the starting CNC film, or by forming a CNC film with gradient color, through masked evaporation, we were able to prepare encoded stretchable chiral nematic CNC-elastomers.
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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".