Positive feedback technique and split‐length transistors for DC‐gain enhancement of two‐stage op‐amps
Bibliographic record
Abstract
This study presents the design and simulation of a fully differential two‐stage op‐amp in a 0.18 μm complementary metal–oxide–semiconductor process with a 1.8 V supply voltage. In this op‐amp, positive feedback technique and split‐length transistors (SLTs) are employed to increase the DC‐gain of the op‐amp by about 22 dB without affecting the unity‐gain bandwidth (UGBW), stability, power dissipation and output voltage swing of the conventional two‐stage op‐amp. A comprehensive analysis is provided for differential‐mode gain, common‐mode gain, power supply rejection ratio, input‐referred noise, input offset, frequency response and the effect of using SLTs on DC‐gain sensitivity. The proposed op‐amp is utilised in a flip‐around sample‐and‐hold amplifier (SHA). The output spectrum of the SHA shows the total harmonic distortion of 0.0023%. The post‐layout and Monte Carlo simulation results show that the proposed op‐amp has better performance than the state‐of‐the‐art designs.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".