Novel Highly Tunable MEMS Capacitors With Flexible Structure and Linear C-V Response
Bibliographic record
Abstract
MEMS parallel-plate tunable capacitors are widely used in different areas such as tunable filters, resonators and communications (RF) systems for their simple structures, high Q-factors and small sizes. However, these capacitors have relatively low tuning range (50%) and are subjected to highly sensitive and nonlinear capacitance-voltage (C-V) responses. In this paper novel designs are developed which have C-V responses with high linearity and tunability and low sensitivity. The designs use the flexibility of the moving plates. The plate is segmented to provide a controllable flexibility. Segments are connected together at end nodes by torsional springs. Under each node there is a step which limits the vertical movement of that node. An optimization program finds the best set of step heights that provides the highest linearity. Two numerical examples of three-segmented- and six-segmented-plate capacitors verify that the segmentation of moving plate can considerably improve the linearity without decreasing the conventional tunability. A two-segmented-plate capacitor is then designed for standard processes which cannot fabricate steps of different heights. The new design uses a flexible step (spring) under middle node. The simulation of a capacitor with flexible middle step, designed for PolyMUMPs process, demonstrates a C-V response with high tunability and linearity and low sensitivity.
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 | 0.000 |
| Open science | 0.001 | 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".