Preparation of Eco-Friendly Nanocatalyst Calcium Oxide (CaO) for Oily Wastewater Treatment by Advanced Oxidation Process
Bibliographic record
Abstract
In the present work, a novel eco-friendly nanocatalyst (NC) calcium oxide (CaO) is synthesized from the waste of tomato plants by physical method for the degradation of oil in oily wastewater by photocatalytic technology as a sophisticated oxidation process. The characterization of NC prepared is described by dynamic light scattering (DLS), Brunauer-Emmett-Teller (BET) analysis, Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), X-ray powder diffraction (XRD), and energy-dispersive X-ray (EDX) spectroscopy, which illustrated that the NC prepared possessed a nanoscale size and a cubic crystal structure. The activity of NC in the photodegradation process is evaluated using oil concentration (100–500 ppm), amount of NC (0.1–1) g/L, and pH (4–12) at a specific aeration rate of 1 L/min and time irradiation of 30–180 min and under UV light. The findings showed that the degradation efficiency of oil increased with an increased amount of NC, time, and pH while decreasing with increased oil concentration. The maximum degradation of oil reached 83.0% at optimum conditions (oil concentration = 100 ppm, amount of NC = 0.6 g/L, pH = 7, time of irradiation = 120 min, and temperature = 23 ◦C). This work illustrates that the novel NC can be employed as an environmentally friendly and economical photocatalyst and might be improved in its characteristics and performance by thermal technique (calcination) to enhance the reduction of oil from oily wastewater.
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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 | 0.000 | 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) | 0.000 | 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".