A Low‐Cost Simple Sliding Triboelectric Nanogenerator for Harvesting Energy from Human Activities
Bibliographic record
Abstract
Abstract A new sliding triboelectric nanogenerator (TENG) with multiple friction interfaces has been developed. The use of off‐the‐shelf polyethylene terephthalate (PET) and Kapton films as the triboelectric materials, the adoption of cost‐effective flexographic printing as the electrode deposition technique, and the avoidance of expensive and time‐consuming surface treatments render the new TENG easy‐to‐fabricate and inherently low cost. The new sliding TENG generates a surface charge density comparable with the previously reported multilayer sliding TENG whose triboelectric surfaces were modified with expensive and time‐consuming plasma etching for improved triboelectrification. Coupled with the freedom of varying the lateral size and the number of friction interfaces, the new sliding TENG can directly light up hundreds of LEDs, or sustainably power small wearable and portable electronics when integrated with a capacitor through a rectifier. When the new sliding TENG is wrapped around with rubber bands in longitudinal direction, it transforms into a stretchable TENG and is able to harvest energy from tensile motion associated with many human activities.
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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) | 0.000 | 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) | 0.001 | 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".