A 10-bit 110 kS/s 1.16 <inline-formula> <tex-math notation="TeX">$\mu\hbox{W}$</tex-math> </inline-formula> SA-ADC With a Hybrid Differential/Single-Ended DAC in 180-nm CMOS for Multichannel Biomedical Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A 10-bit 110-kS/s successive-approximation analog-to-digital converter (ADC) for multichannel biomedical applications is presented. In order to achieve low-power operation, the ADC utilizes a reduced-speed dynamic comparator, a low-complexity calibration technique, a hybrid single/differential digital-to-analog converter architecture, and an attenuation capacitor with low sensitivity to mismatch errors. Fabricated in 180-nm CMOS, this ADC consumes a total power of 1.16 μW from 1.5 V/1.2 V analog/digital power supplies. The integral nonlinearity is between -1.23 LSB and 1.19 LSB, whereas the differential nonlinearity is between -0.71 LSB and 0.92 LSB. The ADC signal-to-noise-and-distortion ratio and spurious-free dynamic range are 56.1 and 67 dB with a 39.5-kHz sinusoid input, respectively. The ADC figure-of-merit is of 20 fJ per conversion step, which is very competitive, as compared with state-of-the-art ADCs in similar 180-nm CMOS technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it