Low‐frequency nanocomposite piezoelectric energy harvester with embedded zinc oxide nanowires
Bibliographic record
Abstract
Abstract Sweeping developments in microelectromechanical systems and low power electronics have pushed the need for piezoelectric energy harvesters (PEHs). Increasing environmental and biocompatibility issues have drawn interest in lead‐free piezoelectric materials. In this paper, cantilever‐type PEHs at centimeter scale have been proposed to harvest the energies of low‐frequency vibrations caused by a human's movements. The proposed PEHs are made of a passive PDMS substrate sandwiched between two active nanocomposite layers with embedded piezoelectric zinc oxide (ZnO) nanowires. Moreover, two different morphologies including PEHs with constant and tapered thicknesses have been considered. The material properties of such piezoelectric nanocomposites are calculated by an electromechanical model. Afterward, these novel PEHs have been developed in COMSOL Multiphysics and their static and dynamic performances have been investigated. The static study shows that tapered PEHs endures lower stresses. However, the dynamic study discloses that the rectangular design outperforms the tapered one in electrical power and resonance frequency. It is found that the rectangular design can produce 4.1623 μW at the resonant frequency of 25.8 Hz.
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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 | 0.000 |
| 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".