The Effect of Composition on the Properties and Application of CuO-NiO Nanocomposites Synthesized Using a Saponin-Green/Microwave-Assisted Hydrothermal Method
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Bibliographic record
Abstract
In this study, we explored the formation of CuO nanoparticles, NiO nanoflakes, and CuO-NiO nanocomposites using saponin extract and a microwave-assisted hydrothermal method. Five green synthetic samples were prepared using aqueous saponin extract and a microwave-assisted hydrothermal procedure at 200 °C for 30 min. The samples were pristine copper oxide (100C), 75% copper oxide-25% nickel oxide (75C25N), 50% copper oxide-50% nickel oxide (50C50N), 25% copper oxide-75% nickel oxide (25C75N), and pristine nickel oxide (100N). The samples were characterized using FT-IR, XRD, XPS, SEM, and TEM. The XRD results showed that copper oxide and nickel oxide formed monoclinic and cubic phases, respectively. The morphology of the samples was useful and consisted of copper oxide nanoparticles and nickel oxide nanoflakes. XPS confirmed the +2 oxidation state of both the copper and nickel ions. Moreover, the optical bandgaps of copper oxide and nickel oxide were determined to be in the range of 1.29-1.6 eV and 3.36-3.63 eV, respectively, and the magnetic property studies showed that the synthesized samples exhibited ferromagnetic and superparamagnetic properties. In addition, the catalytic activity was tested against para-nitrophenol, demonstrating that the catalyst efficiency gradually improved in the presence of CuO. The highest rate constants were obtained for the 100C and 75C25N samples, with catalytic efficiencies of 98.7% and 78.2%, respectively, after 45 min.
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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 | 0.002 | 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 | 0.001 | 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 it