Development of electrothermal actuator (ETA) with low activation voltage
Bibliographic record
Abstract
Electrothermal actuators (ETAs) are novel active materials that can generate different kinds of motions by thermal expansion induced from Joule heating. The degree of expansion, which influences the deformation and response force, is determined by the coefficient of thermal expansion (CTE) of the material. In order for the material to be activated, it is necessary to create conductive network for Joule heating to take place. As a result, one of the most common methods for creating ETAs is to insert high electrical and thermal conductive filler into the matrix, which allows for fast and uniform heat distribution though out the material, thus initiate the actuation. In this study, we present the characterization results of newly developed ETA composites that has ultra-low activation voltage requirement (9V). To create the novel ETA composites, polydimethylsiloxane (PDMS) is coated to conductive networks which are constructed from high electrical conductive fillers such as carbon nanotubes. The actuation performance of the novel ETA composites is characterized in terms of the conductive network distribution, CTE, heat capacity, change in thermal gradient, and its actuation behaviour.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".