A low-power 10-bit 50-MS/s SAR ADC using a parasitic-compensated split-capacitor DAC
Bibliographic record
Abstract
This paper presents a low-power 10-bit 50-MS/s successive approximation register (SAR) analog-to-digital converter (ADC). To reduce power and area, the monotonic switching procedure is combined with a parasitic-compensated split-capacitor DAC that also has an improved capacitor matching. The nonlinearity of the conventional split-capacitor DAC due to parasitic capacitance and capacitor mismatch is improved by modifying the capacitor bank so that the bridge capacitor is an integer multiple of the unit capacitor (as opposed to fractional multiple in the conventional circuit) and by including two dummy unit capacitors connected to ground. The proposed 10-bit ADC is designed and simulated using a 90-nm CMOS technology. Post-layout simulation results show that at 1.0-V supply and 50 MS/s, the ADC achieves a signal-to-noise-and-distortion ratio (SNDR) of 60.10 dB and consumes 0.32 mW with an input capacitance of 0.48 pF, resulting in a figure of merit (FoM) of 8.44 fJ/conversion-step. The ADC core occupies an active area of 215 × 215 µm2
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".