Nonquasi-Static Effects and the Role of Kinetic Inductance in Ballistic Carbon-Nanotube Transistors
Bibliographic record
Abstract
Nonquasi-static effects in ballistic carbon-nanotube (CN) FETs (CNFETs) are examined by solving the Boltzmann transport equation self-consistently with the Poisson equation. We begin by specifying the proper boundary conditions that should be employed in time-dependent simulations at high speeds; these are the proper boundary conditions for a characterization of the so-called intrinsic transistor, i.e., the internal portion of the device that is unaffected by the source and drain contacts. A transmission-line model that includes both the kinetic inductance (LK) and quantum capacitance (CQ) is then analytically developed from the Boltzmann and Poisson equations, and it is shown to represent the intrinsic transistor's behavior at high frequencies, including a correct prediction of resonances in the transistor'sy-parameters. Finally, we show how to representLKusing lumped elements in the transistor's traditional quasi-static equivalent circuit, and we demonstrate that the resulting circuit is capable of modeling the intrinsic behavior of a ballistic CNFET, including the observed resonances, to frequencies beyond the unity-current-gain frequencyfT. External parasitics can be easily added for an overall compact model of ballistic CNFET operation.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".