Thermal Oxidation of Heavily Deformed Zn Coatings Produced by Cold Spray and Formation of ZnO Nanowires
Bibliographic record
Abstract
Abstract Zinc oxide (ZnO) is known for its rich diversity of microstructures and has been attracting attention for its unique combination of mechanical and physical properties. It has been a material of interest in different areas such as optoelectronics, sensors and the general ceramic industry. It also has been a material of interest in biomedicine due to its antimicrobial characteristics and biocompatibility properties. A simple processing route to produce ZnO micro/nanostructures is the thermal oxidation of zinc, which results in a wide range of ZnO nanostructures depending on the oxidation conditions. The main objective of this study was to investigate the influence of a severe plastically deformed zinc microstructure on the formation of ZnO nanostructures produced by oxidation, with a special attention to the zinc oxide growth mechanism and nanostructures characteristics. For this purpose, the cold spray process was used to produce Zn coatings using different feedstock powders that required different process parameters in order to obtain Zn coatings with severely deformed particles. A non-catalytic thermal oxidation method was then used to successfully produce ZnO nanostructures at the surface of the heavily deformed cold sprayed Zn coatings. The as-grown ZnO nanostructures were investigated in detail using scanning electron microscopy and X-ray photoelectron spectroscopy. These investigations revealed that the chemical fingerprint of the oxides grown in the cold sprayed samples was different from that of conventional ZnO. It was also observed that in the oxidized cold sprayed Zn coatings, the formation of ZnO nanowires was hindered due to the formation of blisters generated during the high temperature exposure, revealing nonoptimized process parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".