Piezoelectric Micro- and Nanostructured Fibers Fabricated from Thermoplastic Nanocomposites Using a Fiber Drawing Technique: Comparative Study and Potential Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We report an all-polymer flexible piezoelectric fiber that uses both judiciously chosen geometry and advanced materials in order to enhance fiber piezoelectric response. The microstructured/nanostructured fiber features a soft hollow polycarbonate core surrounded by a spiral multilayer cladding consisting of alternating layers of piezoelectric nanocomposites (polyvinylidene enhanced with BaTiO3, PZT, or CNT) and conductive polymer (carbon-filled polyethylene). The conductive polymer layers serve as two electrodes, and they also form two spatially offset electric connectors on the fiber surface designed for the ease of connectorization. Kilometer-long piezoelectric fibers of sub-millimeter diameters are thermally drawn from a macroscopic preform. The fibers exhibit high output voltage of up to 6 V under moderate bending, and they show excellent mechanical and electrical durability in a cyclic bend−release test. The micron/nanosize multilayer structure enhances in-fiber poling efficiency due to the small distance between the conducting electrodes sandwiching the piezoelectric composite layers. Additionally, the spiral structure greatly increases the active area of the piezoelectric composite, thus promoting higher voltage generation and resulting in 10−100 higher power generation efficiency over the existing piezoelectric cables. Finally, we weave the fabricated piezoelectric fibers into technical textiles and demonstrate their potential applications in power generation when used as a sound detector, smart car seat upholstery, or wearable materials.
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.
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 | 0.000 | 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) | 0.000 | 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 it