Clay-catalyzed ozonation of endocrine-disrupting compounds in solvent-free media – to better understand soil catalytic capacity
Bibliographic record
Abstract
An original approach never tackled so far allowed correlating the basicity and hydrophilic character of clay catalysts to surface interaction with 17α-Ethinylestradiol (EE2) during ozonation in water. The clay catalysts were found to behave specifically according to their silica/alumina ratio like soils in natural oxidative processes. Acid-activated bentonites (HMt) and ion-exchanged montmorillonite (NaMt and Fe(ii)Mt) showed catalytic activity in the ozonation of 17α-ethinylestradiol (EE2) in aqueous media. In the absence of catalysts, the degradation of (EE2) reached 72% after one minute of ozonation and 99.5% after 60 minutes. In the presence of Fe(ii)Mt, EE2 degradation (96%) was achieved after only one minute of ozonation. Under similar conditions, almost total degradation to 99.99% was registered in 15 minutes of ozonation but without total mineralization of the intermediates. Moderately acid-activated bentonites exhibited higher activity affording total mineralization within a short period of ozonation. The catalytic activity of clay catalysts was found to correlate with their surface basicity and hydrophilic character. The results obtained herein allow understanding soil behavior in natural oxidative degradation of organic molecules and envisaging effective soil-based catalysts with surface properties judiciously tailored according to the nature of organic pollutants in solvent free media.
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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) | 0.001 | 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 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".