Profile design considerations for minimizing base transit time in SiGe HBTs for all levels of injection before onset of Kirk effect
Bibliographic record
Abstract
An iteration scheme to calculate the base transit time (/spl tau//sub b/) for a given collector current density is developed in order to determine the optimal doping profile and Ge profile in the neutral base for minimizing the /spl tau//sub b/ of SiGe HBTs under all levels of injection before the onset of the Kirk effect. We adopt a consistent set of SiGe transport parameters, tuned to measurement data, and include important effects such as the electric-field dependency of the diffusion coefficient and plasma-induced bandgap narrowing in our study. The scheme has been verified with simulation results reported in the literature. Our study shows that under both low and high injection, for a given Ge dose, intrinsic base resistance, and base concentration near the emitter, a retrograde doping profile with a trapezoidal Ge profile gives the minimum /spl tau//sub b/.
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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 | 0.000 |
| 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 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".