Importance of As and Ga Balance in Achieving Long GaAs Nanowires by Selective Area Epitaxy
Bibliographic record
Abstract
We report on the selective area growth (SAG) of GaAs nanowires (NWs) by the catalyst-free vapor-solid mechanism. Well-ordered GaAs NWs were grown on GaAs(111)B substrates patterned with a dielectric mask using hydride vapor phase epitaxy (HVPE). GaAs NWs were grown along the ⟨111⟩B direction with perfect hexagonal shape when the hole’s opening diameter in SiN x or SiO x mask was varied from 80 to 340 nm. The impact of growth conditions and the hole size on the NW lengths and growth rates was investigated. A saturation of the NW lengths was observed at high partial pressures of As 4, explained by the presence of As trimers on the (111)B surface at the NW top surface. By decreasing As 4 partial pressure and decreasing the hole size, high aspect ratio NWs were obtained. The longest and thinnest NWs grew faster than a two-dimensional layer under the same conditions, which strongly suggests that surface diffusion of Ga adatoms from the NW sidewalls to their top contributes to the resulting axial growth rate. These findings were supported by a dedicated model. The study highlights the capability of the HVPE process to grow high aspect ratio GaAs NW arrays with high selectivity.
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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".