On the optimum off-cut angle for the growth on InP(111)B substrates by molecular beam epitaxy
Bibliographic record
Abstract
InGaAs and InAlAs epilayers were grown on InP(111)B substrates by molecular beam epitaxy. Rather than focusing on a specific off-cut angle, the growths were done on rounded wafer edges, which expose a broad spectrum of vicinal surfaces with varying off-cut angle and off-cut azimuth. The epilayers were grown at several different growth conditions by varying the growth temperature, growth rate, and arsenic (As) overpressure. The epitaxial layers were characterized at the center and the edge of the wafers using Nomarski differential interference contrast microscopy and atomic force microscopy. It was shown that a minimum misorientation angle of ∼0.4° should be used in order to avoid pyramidal hillocks. At higher misorientations, 1.7°–3°, step bunching can lead to surface roughening.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".