Degradation and Loss of Antibacterial Activity of Commercial Amoxicillin with TiO2/WO3-Assisted Solar Photocatalysis
Bibliographic record
Abstract
In this study, a TiO2 catalyst, modified with tungsten oxide (WO3), was synthesized to reduce its bandgap energy (Eg) and to improve its photocatalytic performance. For the catalyst evaluation, the effect of the calcination temperature on the solar photocatalytic degradation was analyzed. The experimental runs were carried out in a CPC (compound parabolic collector) pilot-scale solar reactor, following a multilevel factorial experimental design, which allowed analysis of the effect of the calcination temperature, the initial concentration of amoxicillin, and the catalyst load on the amoxicillin removal. The most favorable calcination temperature for the catalyst performance, concerning the removal of amoxicillin, was 700 °C; because it was the only sample that showed the rutile phase in its crystalline structure. Regarding the loss of the antibiotic activity, the inhibition tests showed that the treated solution of amoxicillin exhibited lower antibacterial activity. The highest amoxicillin removal achieved in these experiments was 64.4% with 100 ppm of amoxicillin concentration, 700 °C of calcination temperature, and 0.1 g L−1 of catalyst load. Nonetheless, the modified TiO2/WO3 underperformed compared to the commercial TiO2 P25, due to its low specific surface and the particles sintering during the sol-gel synthesis.
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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 | 0.001 | 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".