Synthesis of New Nitride Alloys with Mg by Plasma‐Assisted Molecular Beam Epitaxy
Bibliographic record
Abstract
A great deal of work is currently devoted to the development of new semiconductor alloys that can expand the range of material properties and device applications. Although group‐III nitride alloys are attractive materials owing to the wide range of tunable direct bandgaps and other suitable properties, the material choices are limited to only a few binary and ternary alloys. This situation is due in part to the limitations of the conventional deposition methods, such as chemical vapor deposition, requiring high temperature and high pressure to synthesize a wider range of metastable alloys. In this context, the synthesis of previously unreported quaternary nitride alloys including Mg—(InGaMg)N—is presented. These alloys, with a tunable bandgap and good crystallinity, extend the group of the materials that may be suitable for the fabrication of optoelectronic devices. The method is based on the conventional plasma‐assisted molecular beam epitaxy (PA‐MBE), using a flux‐modulation technique to enable the incorporation of all elements reaching the growth surface. In addition to detailed experimental characterization of structural and optical properties of the Mg containing nitride alloys, computations on their electronic band structures are also carried out.
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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 | 0.001 |
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".