Quantum capacitance in nanoscale device modeling
Bibliographic record
Abstract
Expressions for the “quantum capacitance” are derived, and regimes are discussed in which this concept may be useful in modeling electronic devices. The degree of quantization is discussed for one- and two-dimensional systems, and it is found that two-dimensional (2D) metals and one-dimensional (1D) metallic carbon nanotubes have a truly quantized capacitance over a restricted bias range. For both 1D and 2D semiconductors, a continuous description of the capacitance is necessary. The particular case of carbon nanotube field-effect transistors (CNFETs) is discussed in the context of one-dimensional systems. The bias regime in which the quantum capacitance may be neglected when computing the energy band diagram, in order to assist in the development of compact CNFET models, is found to correspond only to the trivial case where there is essentially no charge, and a solution to Laplace’s equation is sufficient for determining a CNFET’s energy band diagram. For fully turned-on devices, then, models must include this capacitance in order to properly capture the device behavior. Finally, the relationship between the transconductance of a CNFET and this capacitance is revealed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".