Curve-Shaped Anchor for Durability and Efficiency Improvement of Piezoelectric MEMS Energy Harvesters
Bibliographic record
Abstract
In this paper we propose a new curve-shaped anchoring scheme to improve the durability and energy conversion efficiency of the piezoelectric MEMS harvesters. In this regard, a doubly clamped curve beam with a mass at its center is considered as an anchor, while a straight beam with proof mass is integrated to the center of this anchor. To the best of our knowledge, thus far no study has been done to assess the fatigue damage, which is actually critical to the micro-sized silicon-based piezoelectric harvesters. We have utilized the Coffin-Manson method and finite element modeling (FEM) to comprehensively study the fatigue lifetime of the proposed geometry. By using a micro-fabrication process, our proposed piezoelectric harvester has been fabricated and its capability in harnessing the vibration energy has been examined experimentally. It is found that the harvested energy can be enlarged by a factor of 2.66, while this improvement is gained by the resonant frequency reduction and failure force magnitude enlargement, in comparison with the conventional geometry of the piezoelectric MEMS harvesters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".