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Record W4232806758 · doi:10.21203/rs.3.rs-82229/v1

Desynchronized Liquid Crystalline Network Actuators with Deformation Reversal Capability

2020· preprint· en· W4232806758 on OpenAlexaff
Yao‐Yu Xiao, Zhi‐Chao Jiang, Junbo Hou, Yue Zhao

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsActuatorDeformation (meteorology)Materials scienceComposite materialComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract 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 a novel type of LCN actuator that deforms from shape-1 to shape-2 and then reverses the deformation direction back to shape-1 or to a new shape-3 on heating or under light only, meaning that the actuator can complete 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, which can be realized through asymmetrical crosslinking and/or asymmetrical stretching of the two sides in preparing the LCN actuator. This desynchronized actuation strategy offers new possibilities in developing light-fueled LCN soft robots. In particular, the multi-stage bidirectional shape change can be used to achieve multimodal, light-driven locomotion with different moving speeds from the same LCN actuator by simply varying the light on/off times to confine shape switch in a specific sub-stage.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.036
GPT teacher head0.313
Teacher spread0.276 · 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.

Study designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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