Novel ternary PPy–ZnFe<sub>2</sub>O<sub>4</sub>/fly ash-cenosphere photocatalysts for photodegradation of methyl orange under UV light
Bibliographic record
Abstract
In this study, fly ash cenospheres (FACs), characterized by their floating properties and inherent photocatalytic activity, were used as a carrier to support ZnFe2O4 material and doped with conductive polymer polypyrrole (PPy) to prepare a novel ternary PPy–ZnFe2O4/FACs (PPy–ZF) composite catalyst. X-ray diffraction, Fourier transform infrared spectroscopy, TEM, and scanning electron microscopy were used to characterize the structure, morphology, and optical properties of the samples prepared. In particular, a 20 mg/L methyl orange (MO) solution at pH 4 was given 0.075 g of PPy–ZF catalyst to add, and after 30 min of dark adsorption, followed by irradiation for 180 min, 98.54% of the MO was removed. The material was also shown to have good stability and reusability through three cycles of use. Additionally, the material exhibited good photocatalytic activity for other dyes. The results of photocatalytic experiments showed their significantly enhanced photocatalytic activity toward MO, which was mainly attributed to the synergistic effect of PPy and ZnFe2O4 on the surface of FACs, leading to a high separation efficiency and a low rate of photogenerated charge complexation. In addition, cyclic tests demonstrated the stability and reusability of the composite. The leading role in the photocatalytic degradation of MO was demonstrated by the radical trapping experiment, which showed ·O2 − and h+. The present study can significantly improve the photocatalytic performance of the floating materials of ZnFe2O4/FACs, which is beneficial to solve the current energy crisis and environmental pollution problems. It has certain reference significance to solve the problems of environmental pollution, waste recycling, and catalyst recycling in the future.
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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".