Degradation of rhodamine dye using a modified flow photocatalytic reactor in the presence of external oxidants
Bibliographic record
Abstract
Abstract The current work addresses the challenge of effectively degrading Rhodamine B dye, a common environmental pollutant using a modified zig‐zag flow type photocatalytic reactor with the main objective of process intensification. A detailed study into the effect of initial dye concentration and operating solution pH on the degradation of Rhodamine B elucidated that the Rh B dye degradation was higher at a lower solution pH (pH 2) and at an optimum initial (20 ppm) dye concentration. Among different photocatalysts studied including TiO 2 , ZnO, and CaO, maximum degradation was seen for the TiO 2 with 83.3% at optimum loading of TiO 2 (1 g/L). Lower degradations of 76.2% at 1.5 g/L of ZnO and 65.9% at 1.5 g/L of CaO were seen for other photocatalysts. Additionally, the introduction of oxidants such as hydrogen peroxide and Fenton reagent further intensified dye degradation, with the combined UV/Fenton process achieving maximum degradation of 94.8% and the highest COD removal of 68.4%. Overall, it is recommended to utilize zig‐zag flow design photocatalytic reactor with combined Fenton's reagent for optimal dye degradation.
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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 | 0.001 |
| 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".