Chopper Stabilized, Low-Power, Low-Noise, Front End Interface Circuit for Capacitive CMOS MEMS Sensor Applications
Bibliographic record
Abstract
In this paper, a chopper stabilized fully differential CMOS pre-amplifier circuit is presented. The proposed circuit is designed for sub-atto Farad capacitive CMOS MEMS sensing applications. Chopper stabilization technique is employed to minimize flicker (1/f) noise and offsets in the circuit. The proposed circuit is designed using MIMOS 0.35 ?m AMS CMOS 3.3 V technology and simulation results from Cadence Virtuoso Spectre circuit simulator show that the proposed circuit is able to detect capacitance changes ranging from 0.0375 aF to 37.5 fF, attain an input inferred noise of 0.9 nV/ , gain of 18.1 dB at 3-dB frequency of 5.5 MHz with total power consumption of 0.33 mW.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".