Characterization and dynamic charge dependent modeling of conducting polymer trilayer bending
Bibliographic record
Abstract
Abstract Trilayer bending actuators are charge driven devices that have the ability to function in air and provide large mechanical amplification. The electronic and mechanical properties of these actuators are known to be functions of their charge state making prediction of their responses more difficult when they operate over their full range of deformation. In this work, a combination of state space representation and a two-dimensional RC transmission line model are used to implement a nonlinear time variant model for conducting polymer-based trilayer actuators. Electrical conductivity and Young’s modulus of electromechanically active PEDOT conducting polymer containing films as a function of applied voltage were measured and incorporated into the model. A 16% drop in Young’s modulus and 24 times increase in conductivity are observed by oxidizing the PEDOT. A closed form formulation for radius of curvature of trilayer actuators considering asymmetric and location dependent Young’s modulus and conductivity in the conducting polymer layers is derived and implemented in the model. The nonlinear model shows the capability to predict the radius of curvature as a function of time and position with reasonable consistency (within 4%). The formulation is useful for general trilayer configurations to calculate the radius of curvature as a function of time. The proposed electrochemical modeling approach may also be useful for modeling energy storage devices.
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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".