Linear Artificial Muscle Based on Ionic Electroactive Polymer: A Rational Design for Open‐Air and Vacuum Actuation
Bibliographic record
Abstract
Abstract The development of linear muscle‐like actuators remains a key objective in the field of electroactive polymers (EAPs). While ionic EAPs are promising technologies to develop biomimetic artificial muscles, their reliance on liquid electrolytes for operation typically restricts them to use in bending devices. Seldom have ionic linear actuators been demonstrated in air, and never in vacuum. Here both are demonstrated. A rational approach supported by a theoretical model is described to identify the general conditions allowing the design of ionic actuators with intrinsically linear deformations. The model highlights that linear deformation can occur by combining two electroactive electrodes with different mechanical and/or electromechanical properties. Where previous work on laminated actuators resulted in bending only, here it is shown that by combining one soft and one stiff electrode, or one highly expanding electrode, and the other minimally deforming electrode, 0.55% linear strain is achieved when activated with 2 V. Best combination of electrodes is selected based on electromechanical model predictions. Single actuator fibers are fabricated for experimental validation. Graded force up to 0.18 N has been achieved by bundling together five linear actuators. The resulting artificial muscles operate in open‐air, and also under high vacuum conditions, opening possibilities for space applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".