Liquid crystal elastomers for actuation: A perspective on structure-property-function relation
Bibliographic record
Abstract
Liquid crystal elastomers (LCEs) have long held significant promise as materials for artificial muscles and smart actuators. Recent advancements in this field have introduced innovative LCE structures at various scales, resulting in novel properties and functionalities that further accentuate their actuation advantages, bolstering their potential as future soft actuation systems. The ongoing pursuit of enhanced performance and functionality in LCE actuators, essential for advancing them towards superior material-based machines and devices, is intricately linked to the understanding of the fundamental structure-property-function relationships. This review provides a perspective on these relationships across multiple structural levels, encompassing chemical structures, mesophase structures, and micro-to-macroscale programmed structures. It delves into the impact of various LCE structures on key actuation-related properties, actuation features, and functionalities. This review aspires to provide valuable insights into the design of high-performance LCE actuators, the development of exceptional actuation modes and behaviors, and the expansion of achievable functionality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".