A Linearly Tunable MEMS Capacitor With Segmented Electrode and Enhanced Structure
Bibliographic record
Abstract
This research presents a novel linearly tunable MEMS capacitor with flexible electrode and modified structural stiffness. The capacitor is designed for PolyMUMPs as a standard three-structural-layer fabrication process. The moving electrode is divided into segments interconnected through torsional springs. Under each connecting point (node) two flexible and rigid steps are located. The flexible steps are cantilever beams, and as the bias voltage increases, they touch their corresponding nodes and consequently their stiffnesses are added to the total structural stiffness. This is the core idea of the proposed design to linearize the capacitance-voltage (C-V) response. An analytical model is developed to investigate the behavior of the new capacitor. In this model, the governing equations of the capacitor are numerically solved to obtain the system’s C-V response. An optimization problem with different design variables, such as dimensions of the segments or the beams stiffness coefficients, is solved to maximize the linearity of the C-V curves. The numerical results demonstrate drastic improvement in capacitors performance, where a highly linear C-V response and a maximum tunability of 94% is reached.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".