A Stretchable Multimode Triboelectric Nanogenerator for Energy Harvesting and Self‐Powered Sensing
Bibliographic record
Abstract
Abstract A new type of stretchable triboelectric nanogenerator (TENG) made of a custom‐formulated stretchable conductive composite and an elastomer is reported in this work. The unique structural design allows this stretchable TENG to effectively operate in both pressing and stretching modes. In the pressing mode, the stretchable TENG is able to deliver an open‐circuit voltage of 69 V, a short‐circuit current density of 3.05 mA m−2, and a power density of 23 mW m−2 under loaded conditions. The excellent electrical properties of the stretchable conductive composite under strained conditions render the TENG performance resilient against stretching, with only a 10% decrease in open‐circuit voltage and charge transfer when being subject to 43% strain. In the stretching mode, the TENG exhibits an open‐circuit voltage of 8.4 V, a short‐circuit current density of 0.18 mA m−2, and a power output of 0.19 mW m−2 under loaded conditions. Aside from pressing and stretching, the TENG is responsive to other mechanical deformation such as bending and twisting, with output voltages of 4 and 8 V, respectively. Versatile applications in energy harvesting and sensing, enabled by the multimode operation capability of the stretchable TENG, are demonstrated.
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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".