Photocatalytic Degradation of Myclobutanil and Its Commercial Formulation with TiO<sub>2</sub> P25 in Slurry and TiO<sub>2</sub>/<i>β</i>-SiC Foams
Bibliographic record
Abstract
Viticulture is one of the crops most subject to pest control by fungicides. Their drainage towards the fresh water affects the aquatic environment, the fauna, the flora and especially the human health. It is therefore necessary to find an adequate solution to solve this problem. Heterogeneous photocatalysis is an advanced oxidation method for the degradation and mineralization of organic pollutants in water and air using semi-conductor (e.g., TiO2). TiO2 P25 in suspension (0.75 g·L−1) is used to treat Myclobutanil contaminated water and a commercial formulation Systhane™ 20EW, a fungicide produced by BASF. After 120 min of batch treatment under our conditions (pH = 6.7, Co = 10 mg ·L−1), 96% and 98% of Myclobutanil and Systhane were removed with 94% and 92% mineralization, respectively. In order to avoid the recovery of nanoparticles of TiO2 P25 after treatment, we have taken care of β-SiC foam cells. Under the same experimental conditions, 45% and 56% of Myclobutanil and Systhane degraded after 4 h with mineralization of 29% and 27%, respectively in recirculation in a fixed-light photoreactor by UV-A lamps. These results are very encouraging: filtering is not necessary to separate the catalyst from the treated water, it is very important for large-scale use of this process.
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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".