Integrated Triboelectric Nanogenerators in the Era of the Internet of Things
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
and 85%, respectively, synchronous with multiple energy sources and hybridized designs. Here, a comprehensive review of the design guidelines of TENGs, their performance, and their designs in the context of Internet of Things (IoT) applications is presented. The development stages of TENGs in large-scale self-powered systems and technological applications enabled by harvesting energy from water waves or wind energy sources are also reviewed. This self-powered capability is essential considering that IoT applications should be capable of operation anywhere and anytime, supported by a network of energy harvesting systems in arbitrary environments. In addition, this review paper investigates the development of self-charging power units (SCPUs), which can be realized by pairing TENGs with energy storage devices, such as batteries and capacitors. Consequently, different designs of power management circuits, supercapacitors, and batteries that can be integrated with TENG devices are also reviewed. Finally, the significant factors that need to be addressed when designing and optimizing TENG-based systems for energy harvesting and self-powered sensing applications are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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