Ferroelectric Dipole Electrets Prepared from Soft and Hard PZT Ceramics in Electrostatic Vibration Energy Harvesters
Bibliographic record
Abstract
Aiming at longer stability of surface potential, we propose a ferroelectric dipole electret (FDE) prepared from hard ferroelectric material. We compared output power of electrostatic vibration energy harvester and surface potential stability between FDEs prepared from soft and hard PZT ceramics, as well as a CYTOP polymer electret. The hard FDE showed a seven-fold increase in output power over the soft FDE and nine-fold increase over the CYTOP polymer electret. The hard FDE also showed longer stability of surface potential than that of the soft FDE, whereas the stability of the hard FDE was not yet comparable to that of CYTOP polymer electret. A FDE prepared from harder PZT ceramic (with higher coercive electric field and Curie temperature) may provide more stability in surface potential.
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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 | 0.001 |
| 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".