The effects of improved conductivity on actuation
Bibliographic record
Abstract
In this study, we investigate the effect of enhancing electrical and ionic conductivity of PEDOT:PSS/PVDF/PEDOT:PSS tri-layer actuators on the speed of charging and of mechanical actuation. We treated the conducting polymer films with methanol, then doped the device with ionic liquid electrolyte. For both treated and untreated tri-layer samples, we measured electrical resistance along the length of the film, ionic resistance through the thickness of the structure, and performed cyclic voltammetry to determine volumetric capacitance and the characteristic time constants. We also measured the mechanical displacement-frequency response of the conducting polymer cantilever beams. Our results showed that methanol treatment increased electrical conductivity by 20x and ionic conductivity by 1.7x. This enhancement did not significantly change the cut-off frequencies of the device. However, at frequencies < 1 Hz, we observed less drop-off in displacement amplitude in the treated samples. For the geometries and conductivities used in this study, improving conductivity of PEDOT:PSS contributed to actuation at frequencies above the cut-off frequency. This may have applications for devices that need to actuate at high frequencies, but not necessarily at maximum strain, such as vibrotactile haptic displays.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".