Synthesis of InN@SiO<sub>2</sub> Nanostructures and Fabrication of Blue LED Devices
Bibliographic record
Abstract
We synthesized InN@SiO(2) nanostructures (i.e., nanoparticles and nanowires) by varying the annealing temperature and nitridation conditions of In(2)O(3)@SiO(2) nanoparticles in the presence of ammonia. The In(2)O(3)@SiO(2) nanoparticles were synthesized using a urea-based homogeneous precipitation of indium hydroxide on the surface of the SiO(2) (15 nm) nanoparticles, followed by annealing at 600 °C in air. Subsequently, nitridation of In(2)O(3)@SiO(2) nanoparticles in ammonia at 600 °C for 2 h resulted in InN@SiO(2) nanoparticles. The sizes of InN nanoparticles are ∼5 nm on the silica surface. Nitridation at the same temperature for 3-5 h gave InN nanoparticles of size ∼20 nm. Furthermore, on annealing above 650 °C the InN nanoparticles grew in the form of nanowires. The nanowires are 4-5 μm in length and have a diameter of 100 nm. The photoluminescence peak of both InN@SiO(2) nanoparticles and nanowires is centered at 442 nm (λ(exi) = 325 nm). Subsequently, the surface of InN@SiO(2) nanoparticles was modified by reacting with dodecyltriethoxysilane at 80 °C, which enabled them to be dispersible in toluene. The surface-modified InN@SiO(2) nanoparticles were used to fabricate blue electroluminescence devices which showed blue electroluminescence peak centered at 442 nm. The Commission Internationale de I'Eclairage (CIE) coordinates of InN@SiO(2) nanoparticles are X = 0.15 and Y = 0.13, which is well within the blue region and commercially appropriate.
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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".