Cyclical Electrical Stimulation of Hydrogel Microactuators Employing Parylene-N Coated Electrodes
Bibliographic record
Abstract
This work presents the cyclical actuation of electric field sensitive microscale hydrogels employing dielectric coated coplanar electrodes. Microscale hydrogels are photopolymerized in-situ, and AC frequency-based actuation combined with pulse width modulation enabled controlled manipulation of hydrogel deformation. Stable actuation cycles are achieved with applied electric potentials from 20 Vpk-pkto 40Vpk-pk, with a maximum true strain of 29% and a minimum rise time of 4.7 s. The peak and trough osmotic pressure for each system' s cycle is also analytically determined, with a peak pressure at 40 Vpk-pkof 201.1±38.3 kPa. A plateau in the peak-to-trough true strain is observed above 30 Vpk-pk. For comparative purposes a system without dielectric coated electrodes and employing external syringe pumps is also examined, and stable cyclical actuation was achieved for applied electric potentials of 5 Vpk-pkand 10 Vpk-pk. For this system the maximum stable rise time, true strain, and osmotic pressure are 8.1 s, 57%, and 429.2±81.9 kPa, respectively. The difference between the two systems highlights how optimization of the dielectric layer's thickness and uniformity can further enhance actuation performance. The electronically responsive hydrogel-based cyclical actuator developed within this work could be further employed for microfluidic regulation in portable low-power systems.
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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".