Negative-Capacitance FET With a Cold Source
Bibliographic record
Abstract
The subthreshold swing (SS) of a field-effect transistor (FET) is given by the body factor multiplied by the transport factor and has a limit of$60\text{ mV} \cdot ^{-1}$at room temperature in the case of the MOSFET. To break this SS limit, the negative-capacitance FET (NC-FET) lowers the body factor by using a ferroelectric film in the gate stack, whereas the cold source FET (CS-FET) and the Dirac source FET (DS-FET) lower the transport factor by introducing an electronic bandgap or manipulating the density of states in the injecting source. In this work, we theoretically and computationally investigate the possibility of FETs with both NC and CS/DS so that both the body and transport factors are lowered simultaneously. The new device physics of the negative-capacitance CS-FET (NCCS-FET) is numerically investigated for 2-D monolayer black phosphorus (ML-BP) FETs with the Hf0.5Zr0.5O3ferroelectric material in the gate stack. The device characteristics of six different FETs, the conventional MOSFET, CS-FET, DS-FET, NC-FET, NCCS-FET, and NCDS-FET are calculated and compared. Overall, the NCCS-FET achieves an average SS of$30.1\text{ mV} \cdot ^{-1}$and a minimum SS as low as$7.21\text{ mV} \cdot ^{-1}$; its O N–O FF ratio is about four orders of magnitude higher than that of a conventional MOSFET. The combined effects of NC and CS more efficiently decrease power dissipation.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".