Large-Deflection Effect on Thermoelastic Dissipation of Microbeam Resonators
Bibliographic record
Abstract
In real applications, beam resonators in MEMS/NEMS often vibrate beyond the linear regime. The present paper aims to study the effect of large-deflection on thermoelastic dissipation of doubly-clamped microbeam resonators. Detailed formulas are derived for quality (Q-) factor due to thermoelastic dissipation which depends on the amplitude of vibration deflection. Under adiabatic or isothermal surface thermal conditions, the nonlinear effect of large-deflection on thermoelastic dissipation is demonstrated with a comparison to the results based on linearized small deflection vibration. Our results show that thermoelastic dissipation is reduced monotonically with increasing amplitude of vibration deflection under adiabatic surface condition, while thermoelastic dissipation is increased monotonically with increasing amplitude under isothermal surface condition. Under both adiabatic and isothermal surface conditions, the large-deflection effect on thermoelastic dissipation becomes more significant for higher vibration frequencies than lower ones. For the first time to the best of our knowledge, these results reveal that large deflection has a significant effect on thermoelastic dissipation of microbeam resonators and surface thermal condition plays an important role in the large-deflection effect.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".