Soft capacitor fibers using conductive polymers for electronic textiles
Bibliographic record
Abstract
A novel, highly flexible, conductive polymer-based fiber with high electric capacitance is reported. In its cross section the fiber features a periodic sequence of hundreds of conductive and isolating plastic layers positioned around metallic electrodes. The fiber is fabricated using the fiber drawing method, where a multi-material macroscopic preform is drawn into a sub-millimeter capacitor fiber in a single fabrication step. Several kilometers of fibers can be obtained from a single preform with fiber diameters ranging between 500 and 1000 µm. A typical measured capacitance of our fibers is 60–100 nF m −1 and it is independent of the fiber diameter. Analysis of the fiber frequency response shows that in its simplest interrogation mode the capacitor fiber has a transverse resistance of 5 kΩ m L −1 , which is inversely proportional to the fiber length L and is independent of the fiber diameter. Softness of the fiber materials, the absence of liquid electrolyte in the fiber structure, ease of scalability to large production volumes and high capacitance of our fibers make them interesting for various smart textile applications ranging from distributed sensing to energy storage.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".