Design and synthesis of wide tuning range variable comb drive MEMS capacitors
Bibliographic record
Abstract
Purpose To present a general synthesis method in the design of variable comb drive MEMS capacitors which can provide specified capacitance versus position profiles while give large tuning range. Design/methodology/approach By carefully choosing design parameters and constraint conditions, the design process is implemented as the solution of a constraint optimization problem. An electric field analysis software based on the finite element method and an optimization software based on the evolutionary stochastic search are chosen to work together to implement the system. Findings The results verify that the shape of a variable MEMS capacitor has a great influence on the capacitance versus distance profile and demonstrates that a specific geometry of the MEMS capacitor can be found to match a desired capacitance‐distance profile. Research limitations/implications The analytical expression for the capacitance formed between the fixed and the movable fingers is somewhat inaccurate. The results are not compared to measurement because no device has been fabricated. Practical implications A very successful numerical simulation example and guidance for MEMS designers to develop MEMS devices with variable electrode shapes. Originality/value This paper proposes a systematic way for the design of MEMS tunable capacitors with variable shape. The approach can be used to design MEMS devices with variable electrode shapes to satisfy specific requirements.
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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 | 0.001 | 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".