Emerging Aspects of Photo-catalysts (TiO2 & ZnO) Doped Zeolites and Advanced Oxidation Processes for Degradation of Azo Dyes: A Review
Bibliographic record
Abstract
Background: Azo dyes are recognized as non-decomposable and recalcitrant compounds and can be depleted into more dangerous secondary products in anaerobic environments. In the current scenario, different water treatment strategies, including adsorption, photocatalysis, and advanced oxidation processes based practices, are facing different limitations. Method: A literature survey was accomplished by searching the scientific data from different search engines, including Scopus, PubMed, Science Direct, Springer, Taylor and Francis, Google Scholar, Blackwell-Synergy, Wiley-Interscience and Research-Gate, etc. This article has been compiled after intensively reviewing about 231 research papers, reviews, and book chapters in the fields of industrial effluents, hazardous materials, and water treatment strategies with their advantages and limitations. Results: Molecular oxygen and other active species, such as O2•−, HO2•, H2O2, and •OH, play a significant role in the degradation of dyes in AOPs and photocatalyst utilizes sunlight energy and accelerates some chemical reactions depending upon the activation energies. Different reaction parameters, including calcination temperature, pH, initial dye concentration, and catalyst dosage, have a significant impact on photocatalytic degradation performance. Characterization of degradation processes of dye-stuffs could be carried out by the state-of-the-art analytical techniques i.e. UV-Visible spectroscopy, powdered XRD, FTIR (ATR), EDX-SEM, BET, and differential pulse voltammetry. GC-MS and LC-MS investigation of photodegradation by-products and intermediates could provide identification and possible degradation pathway for target dye molecules. This review covers research related to photocatalytic degradation of azo dyes by TiO2 and ZnO, widely used photocatalysts, and various combinations of zeolites. Conclusion: It can be concluded that the combination of nano-sorbents (Fly Ash Zeolites) and photocatalysts not only enhances the degradation but also effectively removes toxic dye molecules and their by-products. The review explains the suitability of synergic applications of catalysts (TiO2, ZnO) and catalytic bed (zeolites) for different industrial effluents and waste water treatment at a significant pace towards green technology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".