Numerical Investigations of Nanowire Gate-All-Around Negative Capacitance GaAs/InN Tunnel FET
Bibliographic record
Abstract
We demonstrated a nanowire gate-all-around (GAA) negative capacitance (NC) tunnel field-effect transistor (TFET) based on the GaAs/InN heterostructure using TCAD simulation. In the gate stacking, we proposed a tri-layer HfO2/TiO2/HfO2as a high-K dielectric and hafnium zirconium oxide (HZO) as a ferroelectric (FE) layer. The proposed GAA-TFET overcomes the thermionic limitation (60 mV/decade) of conventional MOSFETs’ subthreshold swing (SS) thanks to its improved electrostatic control and quantum mechanical tunneling. Simultaneously, the NC state of ferroelectric materials improves TFET performance by exploiting differential amplification of the gate voltage under certain conditions. The most surprising discoveries of this device, which outperforms all previous results, are the very high$I_{ON}/I_{OFF}$ratio on the order of 1011and the enormous on-state current of 135$\mu \text{A}$. The incorporation of the NC effect with a 9 nm HZO results in the lowestSSof 20.56 mV/dec (52.38% lower than baseline TFET) and the highest voltage gain of 6.58. Furthermore, the output characteristics revealed a large transconductance ($g_{m}$) of 7.87 mS (103order higher than the baseline TFET), drain-induced barrier lowering (DIBL) of 9.7 mV, and a threshold voltage of 0.53 V (37.65% lower than baseline TFET), all of which are significant. Thus, all of the results indicate that the proposed device structure may lead to a new route for electronic devices, creating higher speed and lower power consumption.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".