Facile approach for synthesis of stable, efficient, and recyclable ZnO through pulsed sonication and its application for degradation of recalcitrant azo dyes in wastewater
Bibliographic record
Abstract
In the present study, the ultrasound in pulsed mode was used as a part of an advanced oxidation method. The influence of the pulsed ultrasound mode for the preparation of the zinc oxide (ZnO) wurtzite nanoparticle was investigated. The catalysts synthesized were analysed using SEM, TEM, EDAX, BET surface area, XRD, and DRS to study their morphological and structural characterizations. The ZnO nanoparticles exhibited a highly hexagonal structure from pulsed sonication synthesis route. The efficiency of the decolourization of the reactive red 4 (RR4) dye was studied under different operation parameters such as dye concentration, initial solution pH, oxidant (e.g., H2O2) concentration, and catalyst loading. The hybrid combined process of pulsed sonolysis, pH (4.0), H2O2 (17.64 mmol), and catalyst (0.35 g/L) achieved 97% degradation and 87.5% chemical oxygen demand removal in about 20 min of reaction time. The cyclic degradation studies of RR4 removal with 0.35 g/L of ZnO showed the reusability of catalyst up to the fifth removal cycle with negligible loss in the catalytic performance. GC–MS study, used for the detection of the RR4 intermediates, revealed the oxidation–reduction reaction by the reactive radicals proceeded via the reductive cleavage of the azo bonds. The studied process, based on the pulsed ultrasound, is found to be effective for the degradation of RR4 dye.
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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) | 0.001 | 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".