Extended Scale Length Theory for Low-Dimensional Field-Effect Transistors
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Bibliographic record
Abstract
Low-dimensional (low-D) semiconductors such as carbon nanotubes (CNTs) and 2-D materials are promising channel materials for nanoscale field-effect transistors (FETs) due to their superior electrostatic control. However, classical scale length theory (SLT) does not incorporate the effect of channel extensions, which becomes crucial for thin channels (< 10 nm) and short gate lengths. Here, we extend the classical SLT by introducing two boundary coupling parameters, which describe the impact of gate and drain biases on the source- and drain-channel junction potentials. Moreover, we introduce a general expression for the scale length specifically for low-D FETs. This extended SLT accurately describes electrostatic short-channel effects (SCEs) of low-D FETs, with < 5% error in subthreshold slope over a wide range of parameters versus > <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> error using the classical SLT. The extended SLT is based on three parameters (scale length, gate, and drain boundary coupling parameters) which can be extracted from potential profiles or FET transfer characteristics. In addition, the extended SLT uses analytical closed-form expressions that can be easily included in a compact model to facilitate design-technology co-optimization (DTCO) with low-D FETs to leverage the crucial role of their extensions.
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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) | 0.001 | 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 it