Analytical Modeling of Line-Tunneling TFETs Based on Low-Bandgap Semiconductors
Bibliographic record
Abstract
The combination of two techniques: low-bandgap semiconductor and line-tunneling structure is an effective way to achieve the highest on-current in TFETs. In this paper, design of low-bandgap line-tunneling TEFT and its analytical modeling of drain current equation is proposed. The previously suggested drain current equation for the low-bandgap line-tunneling TEFT has been explained in a relatively complex form based on the minimum tunnel path that is an effective factor in determining band-to-band tunneling (BTBT). It has been simplified in this paper and reformulated based on gate-to-source voltage. Important design factors such as source doping concentration, material and thickness of the gate-insulator were examined by simulation and numerical calculations based on the minimum tunnel path for two low-bandgap In0.88Ga0.12As and relatively high-bandgap GaSb semiconductors. The comparison of the results obtained from simulations with the proposed analytical drain current model show a good agreement. Drain doping concentration, is an effective factor on the off-state current of low-bandgap TFET. This factor was examined in order to reduce the off-current.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".