Mesoporous TiO2 Implanted ZnO QDs for the Photodegradation of Tetracycline: Material Design, Structural Characterization and Photodegradation Mechanism
Bibliographic record
Abstract
A sol-gel method was used to prepare a mesoporous TiO2 implanted with a ZnO quantum dot photocatalyst (TZQ) for the photodegradation of tetracycline (TC) under fluorescent light irradiation. Scanning electron microscopy (SEM) shows the presence of cavities on the photocatalyst surface due to the use of starch as a synthetic template, where the nitrogen sorption results indicate that TZQ contains mesopores with reduced size (ca. 4.3 nm) versus the pore size of the parent meso-TiO2 (ca. 7.5 nm). The addition of ZnO quantum dots (QDs) resulted in spherically-shaped binary composite particles in layers onto the surface of TiO2. The coexistence of the ZnO QDs and TiO2 phase was observed using high resolution-transmission electron microscopy (HR-TEM). The photodegradation of TC was carried out in a homemade reactor equipped with two fluorescent lights (24 W each) and within 90 min of irradiation, 94.6% of TC (40 mg L−1) was photodegraded using 250 mg L−1 of TZQ at pH 9. The major reactive oxygen species identified from the scavenging tests were O2●− followed by HO●. The deconvolution of the photoluminescence spectrum of TZQ indicates the presence of a strong quantum confinement effect (QCE) of the ZnO QDs, a defect related to Ti-species and oxygen. The analysis of the intermediates detected by LC-time-of-flight/mass spectrometry (LC/TOF-MS) suggest two photodegradation pathways. The pathways were validated using the Fukui function approach and the Wheland localisation approach. This simple and efficient photocatalytic technology is anticipated to benefit small-scale animal husbandries and aquaculture operators that have limited access to sustainable water treatment technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".