Preparation and characterization of N–TiO<sub>2</sub> photocatalyst with high crystallinity and enhanced photocatalytic inactivation of bacteria
Bibliographic record
Abstract
This study reports the synthesis, characterization and environmental applications of nitrogen doped TiO2 photocatalyst in the form of powder and film. N-TiO2 photocatalysts were synthesized via the hydrolysis of titanium tetraisopropoxide using urea as the nitrogen source. The crystalline structure, particle size and specific surface area of the resultant N-TiO2 nanoparticles were investigated by x-ray powder diffraction and the Brunauer-Emmett-Teller method. The results showed that a mixture of anatase and brookite phases was formed at pH 1 after annealing the powder at 450 ° C for 4 h, in contrast to a pure anatase phase at pH 3. UV-vis spectral characterization showed that the absorption region of the as-prepared N-TiO2 was extended to the visible light region. Stable sols could be achieved by controlling the molar ratio of water-to-titanium precursor and pH of the sols. During the photocatalytic test, in comparison to the standard commercial photocatalyst Evonik-Degussa P25 and home-made bare TiO2 nanoparticles, the N-TiO2 particles exhibited enhanced photocatalytic performance for degradation of methylene blue (MB) dye. The visible light induced photocatalytic inactivation of the obtained nanopowders and nanofilms on bacteria (Escherichia coli) was evaluated. The N-TiO2 nanomaterials showed higher bactericidal activity under visible light irradiation.
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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) | 0.000 | 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".