Dynamic Shape Change of Liquid Crystal Polymer Based on An Order‐Order Phase Transition
Bibliographic record
Abstract
Liquid crystal actuators conventionally undergo shape changes across an order-disorder phase transition between liquid crystal (LC) and isotropic phases. In this study, we introduce an innovative Liquid Crystal Polymer (LCP) actuator harnessing an order-order LC phase transition mechanism. The LCP film is easily stretchable within the LC phase, facilitated by the π-π stacking of phenyl groups serving as robust physical crosslinking points, and thereby transforms to a stable monodomain structure. The resultant monodomain LCP actuator shows a distinctive reversible dynamic shape change, exhibiting extension followed by contraction along the LC director on cooling. The extension is propelled by the reversible smectic C to smectic A phase transition, and the contraction is attributed to the re-entry to the smectic C phase from smectic A phase. Thermal annealing temperature determines this peculiar dynamic shape change, which occurs during both heating and cooling processes. This pivotal attribute finds manifestation in gripper and flower-shaped actuators, adeptly executing grabbing and releasing as well as blooming and closure motions within a single thermal stimulation. In essence, our study introduces an innovative approach to the realm of LCP actuators, ushering in a new avenue for the design and fabrication of versatile and dynamically responsive LCP actuators.
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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".