Photocatalytic Performance of Titanium Dioxide Thin Films from Polymer-Encapsulated Titania
Bibliographic record
Abstract
The performance of a proprietary catalyst (VN-TiO 2 ) was compared with standard P25 TiO 2 for removal of methylene blue in water using immobilized photocatalysis. Using a fiberglass disk as the support medium dip coated in the VN-TiO 2 solution and calcining, porous films with a high surface area (up to 109 m 2 /g) were produced without any modification. Although films formed with VN-TiO 2 on fiberglass disks had a reaction rate 50% lower than that of P25, the disks coated with VN-TiO 2 were mechanically robust in the reactor, compared to those coated with P25. The addition of only 15 wt % P25 in the VN-TiO 2 solution increased the reaction rate by 40%, while maintaining the mechanical stability. The reuse potential of both catalysts was tested, and the rates of deactivation were comparable for both catalysts. Deactivation occurred due to sustained adsorption of Methylene Blue intermediates, as well as a loss of active sites, because of heat treatment for reactivation. Low-priced fiberglass in combination with the easily impregnable polymer-encapsulated titania is a viable option for producing mechanically robust and uniform catalyst coating for immobilized photoreactors.
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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".