The Sonophotocatalytic Degradation of Pharmaceuticals in Water by MnOx-TiO2 Systems with Tuned Band-Gaps
Bibliographic record
Abstract
Advanced oxidation processes (AOPs) are technologies to degrade organic pollutants to carbon dioxide and water with an eco-friendly approach to form reactive hydroxyl radicals. Photocatalysis is an AOP whereby TiO2 is the most adopted photocatalyst. However, TiO2 features a wide (3.2 eV) and fast electron-hole recombination. When Mn is embedded in TiO2, it shifts the absorption wavelength towards the visible region of light, making it active for natural light applications. We present a systematic study of how the textural and optical properties of Mn-doped TiO2 vary with ultrasound applied during synthesis. We varied ultrasound power, pulse length, and power density (by changing the amount of solvent). Ultrasound produced mesoporous MnOx-TiO2 powders with a higher surface area (101–158 m2 g−1), pore volume (0-13–0.29 cc g−1), and smaller particle size (4–10 µm) than those obtained with a conventional sol-gel method (48–129 m2 g−1, 0.14–0.21 cc g−1, 181 µm, respectively). Surprisingly, the catalysts obtained with ultrasound had a content of brookite that was at least 28%, while the traditional sol-gel samples only had 7%. The samples synthesized with ultrasound had a wider distribution of the band-gaps, in the 1.6–1.91 eV range, while traditional ones ranged from 1.72 eV to 1.8 eV. We tested activity in the sonophotocatalytic degradation of two model pollutants (amoxicillin and acetaminophen). The catalysts synthesized with ultrasound were up to 50% more active than the traditional samples.
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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".