Design and Modelling of Novel Linearly Tunable Capacitors
Bibliographic record
Abstract
MEMS-based tunable capacitors with electrostatic actuation are well-known for their wide tuning ranges, high Q-factors, fast responses, and small sizes. However, tunable capacitors exhibit very high sensitivity near pull-in voltage which counters the concept of tunability. In this research, two novel designs are presented that improve the high sensitivity in capacitance-voltage (C-V) curve. In the first design, the nonlinear deformation of supporting beams is studied to develop a new nonlinear spring. The variable stiffness coefficients of such springs improve the linearity of the C-V curve, and by delaying the pull-in, the maximum tunability is also increased without using complex geometries. In the second design, an asymmetric non-parallel-plate capacitor is introduced, in which the C-V response has lower sensitivity at high voltages. The design concept can be applied to highly tunable capacitors to improve the sensitivity and maintain high tunability. The numerical results demonstrate low sensitivity and high linearity and tunability for the new designs.
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 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 | 0.000 |
| 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".