Design, fabrication, and testing of a low frequency MEMS piezoelectromagnetic energy harvester
Bibliographic record
Abstract
Abstract This paper details a power solution for smart grid applications to replace batteries by harvesting the electromagnetic energy from a current-carrying wire. A MEMS piezoelectromagnetic energy harvester has been fabricated using PZT screen-printing technology with a centrally-supported meandering geometry. The energy harvesting device employs a symmetric geometry to increase its power output by reducing the effects of the torsional modes and the resultant overall strain nodes in the system subsequently reduce the complexities for the electrode fabrication. The unit is modelled using COMSOL to determine mode shapes and frequency response functions. A 12.7 mm by 14.7 mm unit is fabricated by screen-printing 75 μ m-thick PZT on a stainless steel substrate and then experimentally tested to validate the FEA results. Experimentally, the harvester is shown to produce 9 μ W from a wire carrying 7 A while operating at a distance of 6.5 mm from the wire. The design of the current work results in a greater normalized power density than other MEMS based piezoelectromagnetic devices and shows great potential relative to larger devices that use bulk or thin film piezoelectrics.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".