A Model for Mechanical Force Sensing in Conducting Polymers
Bibliographic record
Abstract
Conducting polymers have been shown to work as force sensors in an electrolyte by generating a voltage or current when the force applied to them is changed. One possible sensing mechanism is the change in the polymer capacitance as a result of an induced tension. This change in capacitance can be related to perturbation of Donnan equilibrium potential by external load. In this paper we present a model using this proposition to predict conducting polymer sensing behaviour. The model also takes the dependence of the sensing voltage on the polymer oxidation state into account. The predicted model results are compared with experimental measurements on a free-standing film of polypyrrole in an aqueous electrolyte of NaPF6. Sensing voltages ranging from ~ 80-110 μV were detected in response to 1.72 MPa change in the polymer stress, when the polymer was at oxidation states of -0.2 V to 0.4 V vs. Ag/AgCl reference electrode. The load-dependent capacitance necessary to induce the observed sensing currents and voltages is determined. The cycle life of the polypyrrole mechanical sensor was also studied and it was shown that after an initial transient period, the sensing current amplitude stays constant for at least 5400 cycles.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".