Cesium Lead Halide Perovskite Decorated Polyvinylidene Fluoride Nanofibers for Wearable Piezoelectric Nanogenerator Yarns
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Piezoelectric nanogenerators (PENGs) provide a viable solution to convert the mechanical energy generated by body movement to electricity. One-dimensional yarns offer a platform for flexible wearable textile PENGs, which can conform to body for comfort and efficient energy harvesting. In this context, we report a flexible piezoelectric yarn, assembled by one-step cocentric deposition of cesium lead halide perovskite decorated polyvinylidene fluoride (PVDF) nanofibers, on a stainless-steel yarn. Perovskite crystals were formed in situ during electrospinning. Our work demonstrates a nanofiber morphology in which perovskite crystals spread over the nanofiber, leading to a rough surface, and complementing piezoelectric nanocomposite formation with PVDF for superior stress excitation. We investigated how the halide anions of perovskite affect the piezoelectric performance of PENG yarns by comparing CsPbBr 3 and CsPbI 2 Br. Effects of the perovskite concentration, annealing temperature, and deposition time on the piezoelectric properties of PENG yarns were investigated. Devices assembled with a single yarn of CsPbI 2 Br decorated PVDF nanofibers yield the optimal performance with an output voltage of 8.3 V and current of 1.91 μA in response to pressing from an actuator and used to charge capacitors for powering electronics. After aging in the ambient environment for 3 months, the device maintained its performance during 19,200 cycles of mechanical stresses. The excellent and stable electrical performance can be ascribed to the optimized crystallization of CsPbI 2 Br crystals, their complementing performance with PVDF, and formation of nanofibers with uniformity and strength. The flexibility of piezoelectric yarns enables them to be bent, twisted, braided, and woven for different textile integrations while harvesting energy from body movements, demonstrating the potential for wearable mechanical energy harvesting.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".