Analysis of interaction effects of persulphate and peroxymonosulphate on solar photocatalytic degradation of cortisone acetate
Bibliographic record
Abstract
Abstract The degradation of environmental contaminants using sustainable solar energy is one of the most promising applications of the photocatalytic process. In this research, the individual and interaction effects of persulphate (PS) and peroxymonosulphate (PMS) oxidants on the solar photocatalytic degradation of cortisone acetate (CA) were studied. Concentrations of PS, PMS, and photocatalyst were independent variables, and the response was CA degradation efficiency. Response surface methodology (RSM) and artificial neural network (ANN) models were developed to predict the CA degradation efficiency. The analysis of the current results revealed that the optimum amounts of individual variables were highly affected by the other variables, which confirmed their significant interaction effect. As an example, by increasing the PS concentration, not only were the required concentrations of PMS and photocatalyst decreased, but also the degradation efficiency was enhanced. Then, the overall optimum concentration of the photocatalyst, PS, and PMS were found to be respectively 328.7, 119.1, and 194.2 mg/L using the genetic algorithm method. The maximum CA degradation efficiency at the optimum condition was 95.6% after only 30 min of solar radiation. Finally, investigation of relative importance of the variables showed that the concentrations of both oxidants affected the degradation efficiency almost equally.
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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".