Hydrophobic Properties of CuO Thin Films Obtained by Sol-Gel Spin Coating Technique-Annealing Temperature Effect
Bibliographic record
Abstract
The adhesive characteristics of sol-gel copper oxide (CuO) film surfaces at annealing temperatures ranging from 350 to 550°C were examined in this work. Hydrophobic properties of these oxide film surfaces were studied by contact angle measurements. The surface energy was calculated from contact angle data using harmonic mean method. The structural, morphological and chemical analysis of the samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). The increase in annealing temperature induces a reduction in the hydrophilic properties of the films (adhesive properties). The rise in the hydrophobicity of the CuO surface has been claimed to be explained by a change in interfacial tension. The FTIR spectroscopy analysis revealed that the increase in the annealing temperature eliminates activated neutral species (hydroxyl groups) reacting with the surface of the sample responsible for the wettability. SEM analysis showed that the morphology of the samples is nanostructured containing agglomerates of various forms, a few hundred nanometers in size, randomly dispersed across the surface. The enhanced roughness of the produced film is primarily responsible for the increased hydrophobicity of the films. The XRD data reveal that the films are highly textured and that increasing the annealing temperature induces better layer crystallization and confirms the development of copper oxide CuO.
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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".