Mode localized MEMS transducers with voltage-controlled linear coupling
Bibliographic record
Abstract
Abstract Recent studies have demonstrated mode localized resonant micro-electro-mechanical systems (MEMS) sensing devices with orders of magnitude improvement in sensitivity. Avoided crossings or eigenvalue veering is the physical mechanism exploited to achieve the enhancement in sensitivity of devices operating either in vacuum or in air. The mode localized MEMS devices are typically designed to be symmetric and use gap-varying electrostatic springs to couple motions of two or more resonators. The role of asymmetry in the design of devices and its influence on sensitivity is not fully understood. Furthermore, gap-varying electrostatic springs suffer from nonlinearities when gap variation between coupling plates becomes large due to mode localization, imposing limitations on the device performance. To address these shortcomings, this contribution has two principal objectives. The first objective is to critically assess the role of asymmetry in the device design and operation. We show, based on energy analysis, that carefully designed asymmetry in devices can lead to even higher sensitivities than reported in the literature. Our second objective is to design and implement linear, tunable, electrostatic springs, using shaped combs, which allow large vibration amplitudes of resonators thereby increasing the signal to noise ratio. We experimentally demonstrate linear electrostatic coupling in a two oscillator device. Our study suggests that a future avenue for progress in the mode localized resonant sensing technology is to combine asymmetric devices with tunable linear coupling designs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".