Selective growth and ordering of SiGe nanowires for band gap engineering
Bibliographic record
Abstract
Selective growth and self-organization of silicon-germanium (SiGe) nanowires (NWs) on focused ion beam (FIB) patterned Si(111) substrates is reported. In its first step, the process involves the selective synthesis of Au catalysts in SiO₂-free areas; its second step involves the preferential nucleation and growth of SiGe NWs on the catalysts. The selective synthesis process is based on a simple, room-temperature reduction of gold salts (Au³⁺Cl₄⁻) in aqueous solution, which provides well-organized Au catalysts. By optimizing the reduction process, we are able to generate a bidimensional regular array of Au catalysts with self-limited sizes positioned in SiO₂-free windows opened in a SiO₂/Si(111) substrate by FIB patterning. Such Au catalysts subsequently serve as preferential nucleation and growth sites of well-organized NWs. Furthermore, these NWs with tunable position and size exhibit the relevant features and bright luminescence that would find several applications in optoelectronic nanodevices.
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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 | 0.000 | 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 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".