Hydrogen peroxide‐assisted photocatalysis under solar light irradiation: Interpretation of interaction effects between an active photocatalyst and H<sub>2</sub>O<sub>2</sub>
Bibliographic record
Abstract
Abstract In this work, the combination of H2O2 and an active visible‐light‐driven photocatalyst (Ag‐S/PEG/TiO2) was utilized under natural solar radiation for the degradation of 2‐nitrophenol (2‐NP), and interaction effects between the photocatalyst and hydrogen peroxide were analyzed. For this purpose, experiments were designed using the response surface methodology based on the central composite design. The resulting data was utilized to obtain a model for the prediction of response (the degradation efficiency) as a function of two independent factors (H2O2 concentration and the photocatalyst loading). The statistical analysis indicated that optimum values of each of the two independent factors decreased by increasing the other one and vice versa. Moreover, it was found that adding the optimal amount of H2O2 to the solution, which contained just the photocatalyst, can enhance the degradation significantly (up to 45 %). However, using higher concentrations of H2O2 may decrease the efficiency. The global optimum condition was found to be 545 ppm and 316 mM for Ag‐S/PEG/TiO2 loading and H2O2 concentration, respectively. In this condition, the degradation efficiency of 2‐NP reached 92.4 % after only 45 min of solar light irradiation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 source (direct Gemma or distilled Codex), 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".