Surface Recombination Currents in “Type-II” NpN InP–GaAsSb–InP Self-Aligned DHBTs
Bibliographic record
Abstract
Surface recombination effects are studied in non-passivated non-self-aligned and self-aligned NpN InP-GaAsSb-InP double heterostructure bipolar transistors (DHBTs) down to submicrometer emitter dimensions, and over current densities ranging from 10 A/cm/sup 2/ to 100 kA/cm/sup 2/. The present study is motivated by the drive to scale InP DHBTs for higher speeds and integration densities. Self-aligned InP-GaAsSb-InP DHBTs are characterized by weak emitter size effects (ESEs), and periphery recombination currents are found to be very nearly identical to published results for InP-GaInAs SHBTs despite the major differences in emitter junction band alignments ("type-II" versus "type-I") and injection mechanisms (thermal versus hot electron injection). The correspondence of measured periphery currents in both systems indicates that ESEs are dominated by a mechanism common to InP-GaAsSb and InP-GaInAs devices: this requirement is fulfilled by the direct electron injection from the InP emitter mesa sidewalls onto the extrinsic base surface. Consideration of band alignments and surface depletion effects at the extrinsic base surface is used to explain the commonality of emitter size effects in InP-GaAsSb and InP-GaInAs devices.
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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 | 0.000 |
| 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 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".