Ammonia molecular beam epitaxy growth of p-type GaN and application to bipolar junction transistors
Bibliographic record
Abstract
We have investigated the effect of the growth temperature and magnesium flux on Mg incorporation in ammonia-MBE grown GaN epilayers. Secondary ion mass spectroscopy revealed that the incorporation of Mg is more sensitive to the growth temperature than to Mg flux. Simultaneously, the available amount of Mg at the substrate surface has to be accurately balanced in order to achieve the optimum electrical (p∼3×1017cm−3, μ∼12cm2∕Vs, ρ∼2ohmcm) and structural properties [ω-scan FWHM(0002)∼550arcsec]. The surface morphology of the Mg-doped GaN epilayers, using various growth temperatures and Mg fluxes, has been studied by atomic force microscopy showing a considerable change in the GaN average grain size. The optimum growth window for achieving high quality, p-type conductivity in GaN using ammonia-MBE will be discussed. As an application, n–p–n bipolar junction transistors were grown and fabricated. A current gain of 10 with VBC=0V was achieved using these devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".