Synthesis of Vertically-Aligned Zinc Oxide Nanowires and Their Application as a Photocatalyst
Bibliographic record
Abstract
Vertically aligned zinc oxide (ZnO) nanowires were hydrothermally synthesized on a glass substrate with the assistance of a pre-coated ZnO seeding layer. The crystalline structure, morphology and transmission spectrum of the as-synthesized sample were characterized by X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and ultraviolet-visible (UV-Vis) spectrophotometry, respectively, indicating a wurzite ZnO material of approximately 100 nm wire diameter and absorbance at 425 nm and lower wavelengths. The photocatalytic activity of the sample was tested via the degradation of methyl orange in aqueous solution under UV-A irradiation. The synthesized nanowires showed a high photocatalytic activity, which increased up to 90% degradation in 2 h as pH was increased to 12. It was shown that the photocatalytic activity of the nanowires was proportional to the length to diameter ratio of the nanowires, which was in turn controlled by the growth time and grain size of the seed layer. Estimates suggest that diffusion into the regions between nanowires may be significantly hindered. Finally, the reusability of the prepared ZnO nanowire samples was also investigated, with results showing that the nanowires still showed 97% of its original photoactivity after ten cycles of use.
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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".