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Record W3115856278 · doi:10.1038/s41467-021-20938-6

Desynchronized liquid crystalline network actuators with deformation reversal capability

2021· article· en· W3115856278 on OpenAlexafffund
Yao‐Yu Xiao, Zhi‐Chao Jiang, Yue Zhao

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsActuatorShape changeMaterials scienceDeformation (meteorology)IsotropyPhase (matter)Liquid crystallineLiquid crystalMechanicsComputer scienceOpticsPhysicsComposite materialOptoelectronicsBiophysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Liquid crystalline network (LCN) actuator normally deforms upon thermally or optically induced order-disorder phase transition, switching once between two shapes (shape 1 in LC phase and shape 2 in isotropic state) for each stimulation on/off cycle. Herein, we report an LCN actuator that deforms from shape 1 to shape 2 and then reverses the deformation direction to form shape 3 on heating or under light only, thus completing the shape switch twice for one stimulation on/off cycle. The deformation reversal capability is obtained with a monolithic LCN actuator whose two sides are made to start deforming at different temperatures and exerting different reversible strains, by means of asymmetrical crosslinking and/or asymmetrical stretching. This desynchronized actuation strategy offers possibilities in developing light-fueled LCN soft robots. In particular, the multi-stage bidirectional shape change enables multimodal, light-driven locomotion from the same LCN actuator by simply varying the light on/off times.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.235
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations68
Published2021
Admission routes2
Has abstractyes

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