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Record W2921136850 · doi:10.1117/12.2505826

Liquid-crystal polymer actuators for electrically powered shape change and motion (Conference Presentation)

2019· article· en· W2921136850 on OpenAlexaff
Yue Zhao, Yao‐Yu Xiao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsActuatorMaterials scienceShape changePolymerMechanical engineeringMotion (physics)Presentation (obstetrics)Computer scienceComposite materialElectrical engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this talk, we will report a study of using electric power to trigger programmed shape changes and motions of a liquid crystal polymer network (LCN). The used LCN is a photocrosslinkable main-chain liquid crystal polymer (Tg and clearing temperature near room temperature and 60 oC respectively) that, upon stretching, can undergo large plastic elongation to form monodomain of uniaxial LC orientation before photocrosslinking. By sandwiching thin and flexible conducting wires between a LCN strip and Kapton tape (polyimide film), the resistive heating effect is used to activate the LC-isotropic (order-disorder) phase transition of the LCN and produce reversible bending of the strip at voltage-on and unbending at voltage-off state. The robust, electric field-induced deformation can be repeated for thousands of times without fatigue; and the deformation amplitude and speed are dependent upon the applied voltage. By taking advantage of the great processability of the LCN, complex shapes of the polymer actuator can be prepared at the field-off state. We show that by depositing the conducting wire with Kapton tape in selected areas of the LCN strip (either side or “pattering” on one surface), upon application of a programmed square-wave electric field, versatile shape changes and motions, including locomotion and periodic twisting/unwinding, can be achieved. In certain cases, the electric power is transformed into physical work through the LCN actuation. Possible applications will be discussed.

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 score0.008
Threshold uncertainty score0.028

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)0.0080.002

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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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