Fundamental Material Parameters Governing the Performance of Polymer‐Based Triboelectric Touch Sensors
Bibliographic record
Abstract
ABSTRACT The growing demand for self‐powered electronics, such as touch sensors and wearable devices, highlights the need for reliable and efficient triboelectric systems. However, performance inconsistencies frequently originate from uncontrolled material morphology and processing conditions. This study explores the processing–structure–performance relationships in polymer‐based triboelectric systems, focusing on poly(vinylidene fluoride) (PVDF). Through controlled experiments incorporating auxiliary materials, poly(3‐hydroxybutyrate) (PHB) and carbon nanotubes (CNTs), and characterization via Differential Scanning Calorimetry (DSC), polarized optical microscopy (POM), Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), and scanning electron microscopy (SEM), we demonstrate that triboelectric performance is primarily driven by crystal size reduction rather than increased crystallinity. Additionally, optimized surface morphology, achieved through electrospinning, significantly enhances output by balancing fiber diameter and defect density. This work establishes a systematic framework for interpreting triboelectric behavior, emphasizes the need for standardization and morphological transparency, and provides guidelines for designing high‐performance devices via scalable fabrication methods.
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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".