Nano Groove and Prism-Structured Triboelectric Nanogenerators
Bibliographic record
Abstract
Enhancing the output power of triboelectric nanogenerators (TENGs) requires the creation of micro or nano-features on polymeric triboelectric surfaces to increase the TENGs' effective contact area and, therefore, output power. We deploy a novel bench-top fabrication method called dynamic Scanning Probe Lithography (d-SPL) to fabricate massive arrays of uniform 1 cm long and 2.5 µm wide nano-features comprising a 600 nm deep groove (NG) and a 600 nm high triangular prism (NTP). The method creates both features simultaneously in the polymeric surface, thereby doubling the structured surface area. Six thousand pairs of NGs and NTPs were patterned on a 6×5 cm2 PMMA substrate. It was then used as a mold to structure the surface of a 200 µm thick Polydimethylsiloxane (PDMS) layer. We show that the output power of the nano-structured TENG is significantly more than that of a TENG using flat PDMS films, at 12.2 mW compared to 2.2 mW, under the same operating conditions (a base acceleration amplitude of 0.8 g).
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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".