On the geometrical and mechanical multi-aspect optimization of PPy/MWCNT actuators
Bibliographic record
Abstract
Polypyrrole (PPy) conducting polymers as one of the most well-known actuation materials have shown numerous applications in a variety of fields such as biomedical devices as well as biomimetic robotics. This study investigates the multiobjective optimization of a PPy/MWCNTs actuator through an electrochemomechanical model. The multilayer actuator is composed of a PVDF layer, as the core membrane and an electrolyte reservoir, as well as two one layer of a conjugated polymer and one layer of multiwalled carbon nanotubes deposited on each side of the PVDF layer. In order to obtain the optimum values for each decision variable (i.e., geometrical and electrochemical), the two main outputs of the bending actuator, the tip displacement and blocking force, have been mathematically modeled and formulated as the objective functions. A multiobjective optimization algorithm is applied to simultaneously maximize the blocking force and tip displacement generated by the actuator. Furthermore, a range for each design variable is defined within which none of the objective functions of the film-type actuator dominates the other one while they are both kept within an acceptable range. The results obtained from the mathematical model are experimentally verified. Moreover, in order to determine the performance of the fabricated actuator, its outputs are compared with their counterparts of a neat PPy actuator.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".