Advances in Composite Photocatalysts for Efficient Degradation of Organic Pollutants: Strategies, Challenges, and Future Perspectives
Bibliographic record
Abstract
The persistent release of synthetic dyes such as methylene blue (MB) into aquatic environments poses a significant ecological hazard due to their chemical stability and toxicity. In recent years, the application of engineered composite photocatalysts has emerged as a potent solution for efficient dye degradation under visible and UV light. This review comprehensively summarizes various advanced composites, including carbon-based, metal-doped, and heterojunction materials, tailored for MB degradation. Notably, composites such as TiO2/C-550, WS2/GO/Au, and MOF-derived α-Fe2O3/ZnO achieved near-complete degradation (>99%) within 30–150 min, while others, like ZnO/JSAC-COO− and Ag/TiO2/CNT, displayed enhanced charge separation and stability over five consecutive cycles. Band gap engineering (ranging from 1.7 eV to 3.2 eV) and reactive oxygen species (·OH, ·O2−) generation were key to their photocatalytic performance. This review compares the structural attributes, synthetic strategies, and degradation kinetics across systems, highlighting the synergistic role of co-catalysts, surface area, and electron mobility. This work offers systematic insight into the state-of-the-art composite photocatalysts and provides a comparative framework to guide future material design for wastewater treatment applications.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".