Short channel vertical transistors with excellent saturation characteristics
Bibliographic record
Abstract
The use of a vertical thin film transistor (VTFT) topology in the flat panel active matrix array, opens up a plethora of new high performance applications. The VTFT is small in footprint by virtue of its stacked layer configuration, in which channel lengths can be conveniently scaled down to nanometer regime without having to resort to photolithography as would otherwise be needed when scaling lateral TFTs. More importantly, the VTFT is also fully compatible to the materials and processes used in flat panel technology, takes making it amenable to large area scaling. In the VTFT, the source and drain electrodes are vertically stacked and separated by an intermediate insulator layer. The channel is formed on the vertical sidewall of the source/insulator/drain stack. Since the thickness of intermediate insulator layer defines the channel length, this can now be accurately controlled at the nanometer scale via the thickness of the insulator layer. While nanoscale channel length VTFTs in amorphous silicon (a-Si) have been demonstrated previously, one of the biggest issues was the lack of good saturation behavior at high drain voltages, which made reduction of the gate dielectric thickness mandatory. However, reducing the gate dielectric thickness leads to high gate leakage and early dielectric breakdown. This presentation is on short-channel VTFTs with excellent saturation characteristics, achieved by an ultra-thin silicon nitride (SiN <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> ) gate dielectric using plasma-enhanced chemical vapor deposition (PECVD).
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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 | 0.000 |
| 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 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".