<scp> CeO <sub>2</sub> </scp> / <scp> TiO <sub>2</sub> </scp> / <scp> SiO <sub>2</sub> </scp> nanocatalyst for the photocatalytic and sonophotocatalytic degradation of chlorpyrifos
Bibliographic record
Abstract
Abstract A new nanohybrid photocatalyst named cerium (IV) oxide (CeO 2 )/TiO 2 (titania)/silicon dioxide (SiO 2 ) was firstly synthesized employing the co‐precipitation technique to elaborate the degradation efficiency of chlorpyrifos (CPS) as a relatively indelible organophosphorus pesticide in deionized water in photocatalytic and sonophotocatalytic processes. The influence of various parameters, including photocatalyst dosage, the CPS pesticide concentration, pH, and irradiation time, was investigated, and the optimal parameters for photodegradation and sonophotodegradation were determined. The activity and the electrical energy of this photocatalyst in the photodegradation and sonophotodegradation processes were compared, and it was revealed that the sonophotocatalytic process was superior to the photocatalytic one (about 15%). Results depicted that it can be employed four times for the photocatalytic reactions with the same yield of CPS degradation. Besides, the CPS degradation efficiency at the optimum conditions was found to be 81.1% and 90.8% for the photo‐degradation and sonophotodegradation, respectively. Pursuant to the kinetic studies, the kinetics models that govern these processes are leaner with acceptable accuracy.
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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".