Liquid‐Crystalline Dynamic Networks Doped with Gold Nanorods Showing Enhanced Photocontrol of Actuation
Bibliographic record
Abstract
Abstract A near‐infrared‐light (NIR)‐ and UV‐light‐responsive polymer nanocomposite is synthesized by doping polymer‐grafted gold nanorods into azobenzene liquid‐crystalline dynamic networks (AuNR‐ALCNs). The effects of the two different photoresponsive mechanisms, i.e., the photochemical reaction of azobenzene and the photothermal effect from the surface plasmon resonance of the AuNRs, are investigated by monitoring both the NIR‐ and UV‐light‐induced contraction forces of the oriented AuNR‐ALCNs. By taking advantage of the material's easy processability, bilayer‐structured actuators can be fabricated to display photocontrollable bending/unbending directions, as well as localized actuations through programmed alignment of azobenzene mesogens in selected regions. Versatile and complex motions enabled by the enhanced photocontrol of actuation are demonstrated, including plastic “athletes” that can execute light‐controlled push‐ups or sit‐ups, and a light‐driven caterpillar‐inspired walker that can crawl forward on a ratcheted substrate at a speed of about 13 mm min‐1. Moreover, the photomechanical effects arising from the two types of light‐triggered molecular motion, i.e., the trans–cis photoisomerization and a liquid‐crystalline–isotropic phase transition of the azobenzene mesogens, are added up to design a polymer “crane” that is capable of performing light‐controlled, robot‐like, concerted macroscopic motions including grasping, lifting up, lowering down, and releasing an object.
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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".