Achieving High‐Performance Triboelectric Nanogenerator by DC Pump Strategy
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
Abstract Triboelectric nanogenerator (TENG) has been demonstrated as a promising solution for powering widely distributed electronics in the new era of Internet of Things (IoTs), however, high‐performance TENG always relies on tribo‐materials with high triboelectric property. Herein, a simple self‐charge excitation technique that charge injection is directly realized by self‐generated electrostatic breakdown charge instead of voltage‐multiplying circuit is proposed to break through the limitation of triboelectrification. By using the designed electrostatic breakdown charge excitation TENG (EBE‐TENG), the output performance of poor tribo‐material based TENG such as polyethylene (PE) can be enhanced by 5.7 times, which even approximates that of high tribo‐material based TENG such as fluorinated ethylene propylene (FEP). Moreover, electrostatic breakdown charge excitation technique also exhibits a universal applicable ability for other different triboelectric materials. This work not only greatly simplifies the charge excitation system, but also broadens the availability of materials for achieving high‐performance TENG.
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) | 0.001 | 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 it