Preparation of TiO<sub>2</sub>/Bio-Composite Film by Sol-Gel Method in VOCs Photocatalytic Degradation Process
Bibliographic record
Abstract
Biodegradable of polylactic acid (PLA), polybutylene adipate-co-terephthalate (PBAT) and polybutylene succinate (PBS), which were biodegradable aliphatic polyesters, composite films were contained with titanium dioxide (TiO 2 ) as a photocatalyst to evaluate the photocatalytic activity of bidegradable composite films for toluene removal. The synthesized TiO 2 was prepared by sol-gel method between titanium isopropoxide with acetic acid. To form the anatase structure, it was calcined at 500°C. TiO 2 were added to PLA/PBAT/PBS as a biopolymer blend at 0, 5 and 10 wt% .The TiO 2 /Bio-composite films were fabricated via blown film technique to produce 40 μm films. Photocatalytic activity efficiency of TiO 2 /Bio-composite films was performed in an annular closed system under UV light. Since the amount of TiO 2 affected the efficiency of the photocatalytic activity, this work was mainly concentrated on the effort to embed the high amount of TiO 2 in the biopolymer matrix. The developed photocatalyst was characterized by XRD, UV-Vis spectrophotometer and SEM. The SEM images revealed the high homogeneity of the deposition of TiO 2 on the biopolymer matrix. The X-ray diffraction (XRD) ensures the deposition of TiO 2 as crystalline anatase phase. In addition, the photocatalytic results shown that the toluene removal efficiencies increased with an increasing TiO 2 dosages at 0 wt%, 5 wt%, and 10 wt% , respectively. As aspects, the photocatalytic degradation results showed the highest tolune photocatalytic degradation efficiency of 52.0% at 10 wt% TiO 2 .
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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) | 0.001 | 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 | 0.001 |
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".