Degradation of methyl orange by TiO<sub>2</sub>/polymeric film photocatalyst
Bibliographic record
Abstract
Degradation of methyl orange (MeO), as a model compound, in the presence of immobilized polymeric titanium dioxide (TiO2) catalyst was investigated. Degussa P25 TiO2, Polyvinyl alcohol, and Polyvinylpyrolidone were used to prepare polymeric film immobilized photocatalyst. The photocatalyst pore size varied between 50 and 300 µm while its pore density ranged from 7 to 10 pores per square mm. Adsorption of MeO over the catalyst film followed the Langmuir adsorption isotherm. The degradation kinetics of MeO followed the well‐known Langmuir–Hinshelwood (L–H) type model. The degradation rate increased at higher initial concentrations while flow rate had a negative impact on the degradation rate. pH of the solution influenced the degradation rate, with higher degradation rates observed in acidic solutions. Degradation rate was also increased with increasing light intensity up to a certain level, beyond which it remained almost unchanged. Total organic carbon (TOC) content of MeO was also measured during the degradation process. It was observed that the TOC decreased substantially with time. The degradation efficiency was 85 %.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".