Thermoelastic Damping in Micromechanical Resonators with a Proof Mass and a Network of Suspension Beams
Bibliographic record
Abstract
Predicting thermoelastic damping is crucial for the design of highQmicromechanical resonators. In the past, for microresonators which consist of a proof mass and a network of suspension beams, some experiments showed that Zener's model [Phys. Rev. 52 (1937) 230; Phys. Rev. 53 (1938) 90] and Lifshitz and Roukes' model [Phys. Rev. B 61 (2000) 5600] can give a reasonable prediction, and others experiments showed that the two models fail to give a reasonable prediction. Few works give a reasonable and detailed explanation for this phenomenon. In this paper, a general proof is presented that shows Lifshitz and Roukes' model is valid for microresonators with a proof mass support by a network of suspension beams if all suspension beams are operated at pure bending vibration and all suspension beams have the same thickness. The accuracy of Lifshitz and Roukes' model is verified by comparing its results with the experimental results available in the literature.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".