Selective Area Epitaxy of GaN Nanostructures: MBE Growth and Morphological Analysis
Bibliographic record
Abstract
This work presents the selective area epitaxy of GaN nanostructures grown on Ga-polar GaN/sapphire substrates by plasma-assisted molecular beam epitaxy. We demonstrate three types of nanostructures, including nanowires, nanofins, and nanorings on GaN-on-sapphire templates as well as investigate the ways of controlling their morphology, and orientation of sidewall plus top facets. A range of growth conditions including low to high Ga flux were employed during selective area epitaxy to develop these nanostructures with homogenous geometry and near vertical and smooth sidewalls. Using appropriate growth conditions and mask patterning orientations, nonpolar nanofin grids containing both/either m -/ a -planes with as low as 260 nm fin width and up to six interconnects are demonstrated with smooth sidewalls. Based on these experimental results, we developed a growth model that takes different sidewall facets and orientations into account. The model generalizes the experimental results well and explains the growth conditions for the nanostructures. This study serves to advance the understanding of selective area epitaxy for defining complex III-nitride nanostructures that constitute an active area of research and development in the fields of nanotechnology and nanoscience.
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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".