Design of active temperature compensated composite free-free beam MEMS resonators in a standard process
Bibliographic record
Abstract
Frequency references are used in almost every modern electronic device including mobile phones, personal computers, and scientific and medical instrumentation. With modern consumer mobile devices imposing stringent requirements of low cost, low complexity, compact system integration and low power consumption, there has been significant interest to develop batch-manufactured MEMS resonators. An important challenge for MEMS resonators is to match the frequency and temperature stability of quartz resonators. We present 1MHz and 20MHz temperature compensated Free-Free beam MEMS resonators developed using PolyMUMPS, which is a commercial multi-user process available from MEMSCAP. We introduce a novel temperature compensation technique that enables high frequency stability over a wide temperature range. We used three strategies: passive compensation by using a structural gold (Au) layer on the resonator, active compensation through using a heater element, and a Free-Free beam design that minimizes the effects of thermal mismatch between the vibrating structure and the substrate. Detailed electro-mechanical simulations were performed to evaluate the frequency response and Quality Factor (Q). Specifically, for the 20MHz device, a Q of 10,000 was obtained for the passive compensated design. Finite Element Modeling (FEM) simulations were used to evaluate the Temperature Coefficient of frequency (TCf) of the resonators between -50°C and 125°C which yielded +0.638 ppm/°C for the active compensated, compared to -1.66 ppm/°C for the passively compensated design and -8.48 ppm/°C for uncompensated design for the 20MHz device. Electro-thermo-mechanical simulations showed that the heater element was capable of increasing the temperature of the resonators by approximately 53°C with an applied voltage of 10V and power consumption of 8.42 mW.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".