An ultrasound-assisted photocatalytic treatment to remove an herbicidal pollutant from wastewaters
Bibliographic record
Abstract
Pollutants of emerging concern contaminate surface and ground water. Advanced oxidation processes treat these molecules and degrade them into smaller compounds or mineralization products. However, little information on coupled advanced oxidation techniques and on the degradation pathways of these pollutants is available to identify possible ecotoxic subproducts. In the present work, we investigate the ultrasound assisted photocatalytic degradation pathway of the herbicide Isoproturon. We worked in batch mode in a thermostatic glass reactor. We compared the activity of nanometric TiO2 P25 with that of Kronos 1077, a micrometric TiO2. We discuss the individual, additive and synergistic degradation action of photolysis, sonolysis, sonophotolysis, and sonophotocatalysis by varying catalyst loading and/or ultrasound power for the last three techniques. With 0.1 g L−1 catalyst, photocatalysis and sonophotopcatalysis completely degrade Isoproturon within 240 min and 60 min, respectively (>99% conversion). Sonophotocatalysis breaks Isoproturon down into smaller molecules than photocatalysis alone.
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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) | 0.000 | 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 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".