Investigation of MTBE degradation using advanced oxidation technologies: UV/H2O2, UV/TiO2, and UV/TiO2/H2O2
Bibliographic record
Abstract
Methyl tert-butyl ether (MTBE) present in drinking water sources poses a potential threat to human health. In this study, three advanced oxidation processes (AOPs) were investigated for MTBE degradation: UV/H 2O2, UV/TiO2, and UV/TiO2/H2O 2. MTBE degradation was found to follow the pseudo-first-order kinetics in all the three processes, and the rate constant (k) was affected by the concentrations of H2O2 and TiO 2. But higher concentration levels demonstrated a diminishing return on the reaction rate since excessive H2O2 would act as ·OH scavenger and more TiO2 would block the light passage. The addition of H2O2 to the UV/TiO2 system displayed a negative influence on MTBE degradation compared to the UV/TiO 2 system. Increasing light intensity enhanced MTBE degradation in the UV/H2O2 process (k prop; IavgH) and the UV/TiO2 processes (k prop; IavgT). Two mathematical models were proposed to estimate the rate constants with respect to the average light intensity in the solution (I avgH) and H2O2 concentration in the UV/H 2O2 process, and average light intensity in the solution (IavgT) and TiO2 concentration in the UV/TiO2 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) | 0.001 | 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".