Alumina–Nano-Nickel Composite Coatings on Al6061 Substrate Obtained by Electrophoretic Deposition
Bibliographic record
Abstract
Ceramic–nano-metallic composite coatings of Al2O3–nano-Ni on an aluminum substrate (Al6061) were obtained using electrophoretic deposition (EPD). Three composite coatings with different ratios of nano-Ni, i.e., 25, 50, and 75%, were obtained. The phase composition of the resulting composite coatings was examined using XRD; this confirmed the existence of alumina and nickel in the composite coatings. The surface morphology and microstructure of the composite coatings were analyzed with SEM, while the chemical composition and phase content were determined through energy-dispersive spectroscopy. The hardness indenter results revealed a high hardness 420 HV for the Ni 25% composite coating However the hardness decreased with an increase in the Ni nanoparticle ratio, reaching a value of 360 HV for the Ni 75% composite coating. Reflectance measurements were conducted using a UV–visible spectrophotometer equipped with an integrating sphere (UV2600), and the composite coating with a Ni ratio of 75% exhibited the lowest reflectance of UV–visible light at <0.035. These results are promising for subsequent investigations into the absorbance of Al2O3–nano-Ni composite coatings within the sunlight irradiation wavelength range.
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 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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".