Measurement of MEMS beam resonators using electrostatic force microscopy
Bibliographic record
Abstract
Many micro-electromechanical devices have been developed for application in mechanical sensors and actuators, RF devices and telecommunication electronics [1]-[3]. One important application of surface micromachined mechanical resonators, in a wide variety of geometrical configurations, is in beam and comb resonators. MEMS based resonators and filters operating at RF frequencies have been demonstrated [4]. Testing tools for charactering these microstructures are very useful for understanding the actual mechanical properties, the static and dynamic behavior of the device, and for providing feedback for design and process engineers. However, accurate measurements of very small movement (in the scale of nanometers to micrometers) of these micromechanical devices can be challenging. Electrostatic excitation and detection by capacitive, piezo-resistive and piezo-electric methods are frequently utilized due to their practicability and the possibility of co-fabrication with an electrical circuit on a single chip. The disadvantage of these electrical techniques is the parasitic loading problem which can deteriorate accurate measurement of the performance of dynamic microstructures [5]. Optical techniques such as beam deflection and interferometer techniques can provide much better performance since they are noncontact and very sensitive (in nanometer range) [6]. However, the lateral resolution of optical techniques is usually limited by the optical wavelength and the size of the laser focus spot. Optical methods may not be feasible for detecting comb microresonators due to interference from neighboring beams.
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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) | 0.000 | 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".