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Record W4407840243 · doi:10.1002/anie.202500527

Dynamic Liquid Crystal Elastomers for Body Heat‐ and Sunlight‐ Driven Self‐Sustaining Motion via Material‐Structure Synergy

2025· article· en· W4407840243 on OpenAlexafffund
Qing Liu, Zhi‐Chao Jiang, Xue Jiang, Jing Zhao, Ying Zhang, Yue Liu, Yao‐Yu Xiao, Wei Pu, Yue Zhao

Bibliographic record

VenueAngewandte Chemie International Edition · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesState Key Laboratory of Polymer Materials EngineeringNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceLiquid crystalActuatorElastomerArtificial muscleBimorphNanotechnologyIsotropySmart materialMechanical energyOptoelectronicsComposite materialOpticsComputer sciencePhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.518
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.217
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2025
Admission routes2
Has abstractyes

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