Dynamic Liquid Crystal Elastomers for Body Heat‐ and Sunlight‐ Driven Self‐Sustaining Motion via Material‐Structure Synergy
Bibliographic record
Abstract
Abstract Self‐sustained actuators powered by natural, low‐energy sources based on liquid crystal elastomers (LCEs) are attractive as they offer high safety, abundant energy availability, and practicality in applications. However, achieving stable self‐sustaining motion with low‐energy sources requires high actuation strain rates within a narrow temperature range near ambient conditions – a great challenge as LCEs with low nematic‐to‐isotropic transition temperatures (T ni ) generally exhibit reduced actuation strain and strain rates. To address this, we synthesized a carbon nanotube‐doped LCE with a low T ni and reversible Diels–Alder crosslinks, termed DALCE, and readily (re)fabricated it into specific structures (e.g., twisted‐and‐coiled or bimorph shapes). By leveraging material‐structure synergy, we achieved both low T ni and high actuation strain rates, enabling self‐rolling, self‐breathing and autonomous twisting‐untwisting movements powered by ambient/body temperature or natural sunlight. This low‐energy, self‐sustained actuator design opens new possibilities for LCE‐based biomedical applications and naturally powered automatic devices.
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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".