Contact-Separation Triboelectric Nanogenerators with Variable-Angle Motion: An Electromagnetic Approach Based on Maxwell's Equations
Bibliographic record
Abstract
Triboelectric nanogenerators (TENGs), which are primarily based on Maxwell's equations, provide a lightweight, cost-effective approach for energy harvesting and self-powered sensing, particularly excelling in low-frequency mechanical energy conversion. While conventional research primarily focuses on vertical or horizontal contact-separation, a theoretical framework for variable-angle motion remains underdeveloped. This study formulates an electromagnetic model for variableangle contact-separation TENGs using Maxwell's equations, incorporating mechanically induced charge redistribution to refine the theoretical electric potential distribution. Analytical solutions confirm that angular motion can enhance displacement current and energy conversion efficiency. To validate the proposed model, simulated electric potential outputs are compared with experimental results from a prototyped multilayer zigzag TENG structure, demonstrating strong agreement and practical feasibility. These findings provide a robust theoretical foundation for optimizing TENG performance in dynamic mechanical systems, with applications in sustainable energy, mechanical sensing, and IoT devices.
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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 | 0.001 |
| 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".