Photocatalytic degradation of Rhodamine B dye with TiO2 immobilized on SiC foam using full factorial design
Bibliographic record
Abstract
Abstract Textile effluents treatment is one of the important environmental challenges nowadays. Photocatalysis has proven its effectiveness for the removal of recalcitrant compounds, and it is considered as a green technology for the treatment of effluents. However, good photocatalytic yield is strongly related to the operating parameters. In this study, a supported TiO2 on a β-SiC foam was tested for the removal of Rhodamine B (RhB). The photocatalytic discoloration of RhB synthetic solution in our condition was about 90%. The effects of each parameter were assessed through a full factorial design. Sixteen tests were carried out and the response was RhB removal. The most influent parameters were TiO2/β-SiC foam quantity, the concentration of RhB, the volume of H2O2 and pH. Their contributions on RhB removal were, respectively, 53.01, 30.49, 2.7, and 2.48% according to Pareto diagram. Analysis of the coefficients shows that initial concentration of RhB and volume of H2O2 had a negative effect on the response. However, the quantity of TiO2/β-SiC foam and pH had a positive effect on the response. The influence of the flow rate on the process was assessed. The results showed a slight increase in RhB removal. Furthermore, the aging test of TiO2/β-SiC foam on the photocatalytic efficiency was carried out after ten successive photocatalysis tests. Only 6.7% loss of yield was observed. These results are very encouraging for an application at the industrial scale.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".