Direct Synthesis of Oxynitride Nanowires through Atmospheric Pressure Chemical Vapor Deposition
Bibliographic record
Abstract
Binary and ternary oxynitride solid alloys were studied extensively in the past decade due to their wide spectrum of applications, as well as their peculiar characteristics when compared to their bulk counterparts. Direct bottom-up synthesis of one-dimensional oxynitrides through solution-based routes cannot be realized because nitridation strategies are limited to high-temperature solid-state ammonolysis. Further, the facile fabrication of oxynitride thin films through vapor phase strategies has remained extremely challenging due to the low vapor pressure of gaseous building blocks at atmospheric pressure. Here, we present a direct and scalable catalytic vapor-liquid-solid epitaxy (VLSE) route for the fabrication of oxynitride solid solution nanowires from their oxide precursors through enhancing the local mass transfer flux of vapor deposition. For the model oxynitride material, we investigated the fabrication of gallium nitride and zinc oxide oxynitride solid solution (GaN:ZnO) thin film. GaN:ZnO nanowires were synthesized directly at atmospheric pressure, unlike the methods reported in the literature, which involved multiple-step processing and/or vacuum operating conditions. Moreover, the dimensions (i.e., diameters and length) of the synthesized nanowires were tailored within a wide range.
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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".