Wideband, low-noise accelerometer with open loop dynamic range of better than 135DB
Bibliographic record
Abstract
This paper reports a high performance capacitive accelerometer with a noise level of 350ng Hz , bandwidth of 4.5kHz, and 135 dB open loop dynamic range at 1Hz bandwidth. The accelerometer was designed in a mode-tuning structural platform. This platform is developed to address the issue between sensitivity and bandwidth for the low-noise capacitive in-plane accelerometers. The platform proposes to substitute the accelerometer's proof mass with a moving frame. Furthermore, the elastic elements and anchor points are located both inside and outside the moving frame. As such, the mode-tuning structural platform contributes in tuning the resonance frequencies and mode shapes of the accelerometer to acquire higher bandwidths. The proposed platform also addresses the issue of sensitivity by increasing the number of sensing elements located inside and outside the moving frame. To the best of the authors' knowledge, no MEMS accelerometer has been able to offer such a combination of high performance metrics, making this platform a viable candidate for developing high performance accelerometers.
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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) | 0.001 | 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 | 0.001 |
| 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".