Asymmetric lightly doped Schottky barrier CNTFET
Bibliographic record
Abstract
For the first time, an asymmetric lightly doped Schottky barrier carbon nanotube field effect transistor (SB_CNTFETs) is proposed and simulated using quantum simulations. Comparisons are made among four SB_CNTFETs structures for electrical characteristics. One is the conventional SB_CNTFET with an intrinsic channel. The other proposed and studied designations are an asymmetrically doped SB_CNTFET with a doped region near the source only, a symmetrically doped source and drain SB_CNTFETand an asymmetric lightly doped SB_CNTFET which shows the ultimate performance among all. The results show that the new asymmetric lightly doped design decreases significantly the leakage current and thus increases on/off ratio as well as cutoff frequency. It is also demonstrated that this structure possesses two perceivable steps in potential profile of the channel, which lead to another lateral electric field peak inside the channel which leads to the immunity against short‐channel effects. The cutoff frequency characteristics of the four structures of SB_CNTFETs have been discussed. Results show that for channel lengths >30 nm cutoff frequency of the asymmetric lightly doped SB_CNTFETis greater than others. The effect of different doped region lengths in a 30 nm SB_CNTFET has been discussed as well. The proposed new design is promising from several points of view discussed in the study.
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.
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".