Evaluation of modern MOSFET models for bulk-driven 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
With the breathtaking advance of technology, the modern analog/mixed-signal design needs to consider the requirements of low voltage/power and the effects of the MOSFET channel length shrinking. Although a few different schemes have been proposed, the bulk-driven technique, which uses bulk terminal (the fourth terminal of a MOSFET) for signal input, is a promising solution to the low-voltage and low-power applications. However, the conventional MOSFET models are normally set up for the typical gate-driven applications (i.e., using gate terminal for signal input). Besides, due to shrinking MOSFET channels, those MOSFET models may not perform correctly and accurately for the bulk-driven applications, especially in the moderate inversion region. In this paper, we evaluate two MOSFET models including BSIM3V3 and EKV for the bulk-driven applications in a sub-micron CMOS technology. BSIM3V3 is a widely used model in the semiconductor industry, while the EKV model is suitable for the small-channel-length simulation. We focus on several critical MOSFET parameters for bulk-driven application and conduct thorough experiments using the two aforementioned models. The simulation results are analyzed to demonstrate the advantages of the bulk-driven technique compared to the gate-driven scheme in the low-voltage/low-power applications. Finally the performance of the two MOSFET models in the bulk-driven applications is summarized.
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 | 0.000 | 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) | 0.000 | 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