Physical properties of spin-coated nanocrystalline zinc oxide thin film
Bibliographic record
Abstract
ZnO, in its wurtzite structure, is a widely studied metal oxide due to its unique optical and electronic properties, including efficient excitonic emission at room temperature. Zinc oxide thin films were synthesized through the dehydration of various precursors. In ethanol and mono-ethanolamine, zinc acetate (I) and zinc nitrate (II) were dissolved. Glass substrates were coated using the sol-gel spin coating method (3000 rpm for 10 s), followed by heating at 250 °C. This process was done five times to make the films thicker (and allow them to form five layers on the substrate), and then they were annealed at 450 °C for 3 hours in air, yielding 200 nm-thick films. Where acetate-derived ZnO demonstrated superior performance: 92% optical transmission at 1100 nm (vs. 80% for nitrate), a widened bandgap (3.3 eV), and enlarged crystallite size (74 nm), attributed to reduced defect density and homogeneous morphology. The presence of various vibration modes in the prepared samples was also revealed by Raman spectroscopy (RS) of the annealed films. The presence of concentrated stresses within the coated films is also determined using RS, and the scanning electron microscopy results confirm the Raman E2 peaks by FE-SEM images.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".