The Impact of Temperature and Power Variation on the Optical, Wettability, and Anti-Icing Characteristics of AZO Coatings
Bibliographic record
Abstract
The structural, wettability, and optical characteristics of aluminum-doped zinc oxide (AZO) thin films were studied with the objective of understanding the impact of deposition power and deposition temperature. Thin films were deposited using a radio frequency (RF) magnetron sputtering technique. The power output of the RF was augmented from 200 to 260 W, and the temperature was increased from 50 to 200 °C, which led to the development of a (002) peak for zinc oxide. The study of film thickness was carried out using the Swanepoel envelope method from data obtained through the UV-Vis spectrum. An increase in surface roughness value was shown to be connected with fluctuations in temperature as well as increases in deposition power. The findings revealed that as deposition power and temperature increased, the value of optical transmittance decreased, ranging from 70% to 90% based on the deposition parameters within the range of wavelengths that extend from 300 to 800 nm. The wettability properties of the samples were studied, and the maximum contact angle achieved was 110°. A Peltier apparatus was utilised in order to investigate the anti-icing capabilities, which revealed that the icing process was slowed down 3.38-fold. This work extends the understanding of the hydrophobicity and anti-icing capabilities of AZO thin films, specifically increasing both attributes which provide feasible options for purposes requiring resistance to ice.
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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".