ZnO Surface Doping to Enhance the Photocatalytic Activity of Lithium Titanate/TiO2 for Methylene Blue Photodegradation under Visible Light Irradiation
Bibliographic record
Abstract
Wastewater contaminated with dyes produced by textile industries is a major problem due to inadequate treatment prior to release into the environment. In this paper, the ability of ZnO to enhance the interfacial photocatalytic activity of lithium titanate/TiO2 (LTO/TiO2) for the photodegradation of methylene blue (MB) under visible light irradiation (4.38 mW/cm2) was assessed. The ZnO-doped lithium titanate/TiO2 (ZnO/LTO/TiO2) was synthesized using a combination of hydrothermal and wetness impregnation methods. The high-resolution transmission electron microscope (HRTEM) and X-ray Diffraction (XRD) analyses indicate that the ZnO/LTO/TiO2 contain several phases (ZnO, LTO, and TiO2). The adsorption capacity of LTO/TiO2 (70%) was determined to be higher compared to its photocatalytic activity (25%), which is attributed to the strong interaction between the Li and surface oxygen atoms with the MB dye molecules. The introduction of ZnO improved the photocatalytic ability of LTO/TiO2 by 45% and extended the life span of ZnO/LTO/TiO2. The ZnO/LTO/TiO2 can be reused without a significant loss up to four cycles, whereas LTO/TiO2 had reduced adsorption after the second cycle by 30%. The ZnO increased the surface defects and restrained the photo-induced electrons (e−) from recombining with the photo-induced holes (h+). Scavenging tests indicated that the hydroxyl radicals played a major role in the photodegradation of MB, which is followed by electrons and holes.
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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".