Tunable Diffraction Gratings from Biosourced Lyotropic Liquid Crystals
Bibliographic record
Abstract
Diffraction gratings are important for modern optical components, such as optical multiplexers and signal processors. Although liquid crystal (LC) gratings based on thermotropic LCs have been extensively explored, they often require expensive molecules and complicated manufacturing processes. Lyotropic LCs, which can be broadly obtained from both synthetic and natural sources, have not yet been applied in optical gratings. Herein, a facile grating fabrication method using a biosourced lyotropic LC formed by cellulose nanocrystals (CNCs), a material extracted from plants, is reported. Hydrogel sheets with vertically aligned uniform periodic structures are obtained by fixing the highly oriented chiral nematic LC of CNCs in polymer networks under the cooperative effects of gravity on phase separation and a magnetic field on LC orientation. The hydrogel generates up to sixth-order diffraction spots and shows linear polarization selectivity, with tunable grating periodicity controlled through LC concentration regulation. This synthesis strategy can be broadly applied to various grating materials and opens up a new area of optical materials from lyotropic LCs.
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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 | 0.001 |
| 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".