ZnO nanowire growth by chemical vapor deposition with spatially controlled density on Zn<sub>2</sub>GeO<sub>4</sub>:Mn polycrystalline substrates
Bibliographic record
Abstract
Aligned ZnO nanowires were successfully synthesized by CVD growth on polycrystalline Zn 2 GeO 4 :Mn substrates. The density of the nanowires was explored as a function of gold catalyst thickness as well as the geometry of the growth system. For the first time we demonstrated that the density of ZnO nanowires can be directly tailored by adjusting the lateral distance between a Zn 2 GeO 4 :Mn substrate and source powders, and symmetric growth was observed when source powders were placed both upstream and downstream in two separated zones during the synthesis process in a tube furnace. Electric field modelling was employed to predict a desired nanowire density range for future application of the Zn 2 GeO 4 :Mn/ZnO structures to electroluminescent devices.
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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) | 0.000 | 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 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".