Bimetallic nanoporous carbon-based direct-current triboelectric nanogenerators for biomechanical energy harvesting and sensing
Bibliographic record
Abstract
A high-power density direct current triboelectric nanogenerator (DC-TENG) presents a promising solution for sustainable and distributed energy supply in the Industry 4.0 era. This study introduces a contact-separation mode DC-TENG that incorporates core-shell metal-organic framework-derived bimetallic nanoporous carbon (BNPC) as a functional nanofiller in the negative elastomer tribo-layer, significantly enhancing its performance. The BNPC's high surface area and porosity improve dielectric properties and charge trapping, while its bimetallic components suppress charge recombination through interfacial polarization effects. A Kapton-based mechanical rectifier is integrated to enable direct DC output, simplifying system design and enhancing energy utilization. The optimized BNPC@elastomer composite-based DC-TENG (BNDC-TENG) achieves a peak power density of 6.32 W/m 2 . The device demonstrates remarkable durability over 43,000 cycles and can directly charge capacitors and power small electronics. The BNDC-TENG efficiently harvests biomechanical energy from human motion and functions as a self-powered sensor for real-time activity monitoring, including walking and running detection. This work introduces innovative materials and simplified architecture for high-performance DC-TENGs, advancing sustainable energy harvesting and next-generation self-powered sensing applications.
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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 | 0.000 |
| 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) | 0.000 | 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".