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Record W4405918538 · doi:10.1002/smll.202412547

Humidity‐Sensing and Moisture‐Steering Liquid Crystal Elastomer Actuator

2024· article· en· W4405918538 on OpenAlexafffund
Long Xu, Lu Yin, Yue Zhao

Bibliographic record

VenueSmall · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilCentre québécois sur les matériaux fonctionnels
KeywordsHumidityMaterials scienceActuatorElastomerMoistureLiquid crystalComposite materialOptoelectronicsMeteorologyElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

A liquid crystal elastomer (LCE) actuator capable of colorimetric humidity sensing is realized. The designed LCE features acid protonated amino azobenzene side groups in its structure, which endow the actuator with the hygroscopicity and act as the humidity reporter via color changes. Given that the protonated and deprotonated chromophore absorb visible light at different wavelengths, when the protonated LCE is under higher humidity, it absorbs more water that deprotonates azobenzene and leads to a change in color. This humidity-dependent color change is fast, because surface protonation of the actuator is enough. The initial color and the sensitivity to humidity variation are determined by the extent of acid protonation, and the reversible color changes are distinguishable by the naked eye over a wide humidity range. The humidity sensing of LCE actuator in motion is demonstrated using thermally driven rolling rod actuators. Moreover, through spatial-selective exposure of the rolling rod actuator to water mist, the moisture can act as a stimulus to change or reverse the rolling direction and reduce the rolling speed. The achieved nature-inspired colorimetric humidity sensing capability represents an intelligent function for LCE actuators and may widen their application scope.

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: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.607

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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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