Heterogeneous Catalytic Ozonation of Pharmaceuticals: Optimization of the Process by Response Surface Methodology
Bibliographic record
Abstract
Batch heterogeneous catalytic ozonation experiments were performed using commercial and synthesized nanoparticles as catalysts in aqueous ozone. The transferred ozone dose (TOD) ranged from 0 to 150 μM, and nanoparticles were added in concentrations between 0 and 1.5 g L−1, with all experiments conducted at 20 °C and a total volume of 240 mL. A Ce-doped TiO2 catalyst (1% molar ratio of Ce/Ti) was synthesized via the sol–gel method. Response surface methodology (RSM) was applied to identify the most significant factors affecting the removal of selected pharmaceuticals, with TOD emerging as the most critical variable. Higher TOD resulted in greater removal efficiencies. Furthermore, it was found that the commercially available metal oxides α-Al2O3, Mn2O3, TiO2, and CeO2, as well as the synthesized CeTiOx, did not increase the catalytic activity of ozone during the degradation of ibuprofen (IBF) and para-chlorobenzoic acid (pCBA). Carbamazepine (CBZ) and diclofenac (DCF) are compounds susceptible to ozone oxidation, thus their complete degradation at 150 μM transferred ozone dose was attained. The limited catalytic effect was attributed to the rapid consumption of ozone within the first minute of reaction, as well as the saturation of catalyst active sites by water molecules, which inhibited effective ozone adsorption and subsequent hydroxyl radical generation (●OH).
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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 | 0.001 | 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) | 0.001 | 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".