Ionic liquids enhanced performance of PVC gels actuator
Bibliographic record
Abstract
Abstract Stimulated devices are highly demanded for actuators and artificial muscles in the recent era but susceptible to low deformation at an applied voltage. In the present work, ionic liquids (ILs) based gel films were prepared from the polyvinyl chloride (PVC), dibutyl adipate (DBA), 1‐butyl, 3‐methimidazolium chloride, and 1‐pentyl‐3‐methylimidazolium hexafluorophosphate by a simple solvent evaporation method. The structural, morphological, optical, and mechanical properties of the composite PVC/ILs gel were characterized by Fourier‐transform infrared spectroscopy (FTIR), Large Angle X‐ray scattering (LAXS), UV–visible (UV–vis) absorption spectroscopy, scanning electron micrpscopy (SEM) and elemental mapping. We found that the displacement of plasticized PVC gels‐based actuator was 0.1 mm with the response time of 0.33 s at an induced voltage of 1000 V. The loading of 0.02% of IL (fluorides) with PVC gel showed maximum deformation of 0.16 mm with a relatively rapid response time of 0.2 s. These high deformation and response time values of IL fluoride‐based gels are dramatically higher than reported PVC gels. Likewise, the loading of IL fluorides in the PVC gel showed a high elongation value at the break of about 377%. This work suggests that the flexible gel based on IL fluorides and PVC could be a potential candidate for the fabrication of high‐performance artificial muscles and tunable soft actuators.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".