Experimental study of degradation and biodegradability of oxytetracycline antibiotic in aqueous solution using Fenton process
Bibliographic record
Abstract
The degradation of aqueous oxytetracycline (OTC) from an aqueous solution antibiotic using H2O2/Fe2+ process was studied in one 1 L batch chemical reactor. The extent of OTC degradation (20 mg/L) was investigated from a known initial pH solution, temperature and the type of catalyst (Fe2+, Fe3+) and for various initial concentrations of OTC, H2O2 and Fe2+. The degradation efficiency achieved was found to be very important (90.82% and 90.63%) at initial pH solution of 3 and 4, respectively. However, the type of catalyst and the reaction temperature had a slight impact on the final degradation of OTC. The results showed that the OTC removal increased with increasing initial H2O2 concentration in the range of 70 to 150 mg/L and initial Fe2+ concentrations in the range of 2 to 5 mg/L. The highest degradation efficiency obtained at ambient temperature was 90.95% with initial concentration of OTC of 10 mg/L, H2O2 = 150 mg/L and Fe2+ = 5 mg/L. Moreover, biodegradability improved from 0.04 to 0.36 and chemical oxygen demand degradation was 78.35% after 60 min of treatment. This study proved that Fenton process can be used for pretreatment of wastewater contaminated by OTC before a biological treatment. Keywords: Advanced oxidation processes, Chemical degradation, Fenton process, Oxytetracycline, Pharmaceutical wastewater
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".