Shining Light on Liquid Crystal Polymer Networks: Preparing, Reconfiguring, and Driving Soft Actuators
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Soft actuators based on liquid crystal polymer networks (LCNs) have emerged as an exciting research topic due to many envisioned applications in areas such as soft robotics and self‐regulating devices. The infatuation stems from the amazing ability of LCNs to display reversible, large amplitude, and complex shape change as well as locomotion upon a stimuli‐triggered phase transition of mesogens between ordered liquid crystal and disordered isotropic state. Among the various stimuli, light arguably is the most attractive choice. Light can easily be adjusted for its wavelength, intensity, or polarization, structured by means of photomasks or interference patterns, and applied to a target remotely and with high spatiotemporal resolution. Indeed, much research effort is dedicated to LCN actuators that are designed to respond to light in many ways, with light being used not only as an external energy source to drive the shape changes or motion of LCN actuators, but also as a versatile tool in their fabrication and reconfiguration. In this Review, recent achievements are highlighted, a number of important issues are discussed, and critical analysis on the use of light in making, reconfiguring, and driving LCN actuators is provided.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it