Performance improvement of TiO<SUB align=right>2 supported on adsorbents for photocatalytic degradation of MEK in air
Bibliographic record
Abstract
Photocatalytic degradation of Methyl Ethyl Ketone (MEK) was carried out in gas phase using TiO2 supported on different adsorbents. Based on size and surface area, three different adsorbents, montmorillonite, β-zeolite and MCM-41 were tested. A fluidised bed annular photoreactor fitted with either 254 or 365 nm lamps was used for the photodegradation studies. The removal rates of MEK were higher for the catalysts supported on the adsorbent as compared to bare TiO2 (Degussa P25 and sol-gel TiO2) due to both improved adsorption and photocatalytic degradation. The photocatalytic activity of the supported TiO2 was maximum around 50 wt.% loading of TiO2. Among all the adsorbents tested, montmorillonite showed better removal rate than MCM-41 and β-zeolite. Some limited experiments were conducted with Trichloroethylene (TCE) to evaluate the effect of polarity of the organic compound on overall degradation using the supported catalysts.
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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".