Magnetically Separable Fe <sub>3</sub> O <sub>4</sub> /BiOBr Microspheres: Synthesis, Characterization, and Photocatalytic Performance for Removal of Anionic Azo Dye
Bibliographic record
Abstract
Recyclable magnetic Fe3O4/BiOBr microspheres (m-Fe3O4/BiOBr MSs) were synthesized by a simple solvethermal method. The crystals' optical, morphology, and magnetic properties of m-Fe3O4/BiOBr MSs were characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive analysis of X-rays, UV–vis diffuse reflectance spectroscopy, Brunauer–Emmett–Teller, and vibrating sample magnetometry techniques. An anionic dye, Congo red (CR), was selected as a model pollutant to evaluate the photocatalytic activity of m-Fe3O4/BiOBr MSs under simulated solar light irradiation. By calculation, the pseudo-first-order rate constant for photocatalytic degradation of CR was 0.0011 and 0.0046 min−1 using pure BiOBr MSs and m-Fe3O4/BiOBr MSs, respectively. Enhanced photocatalytic activity of m-Fe3O4/BiOBr MSs can result from superior adsorption and transfer performance to organic contaminants in aqueous system. Both the h+ radicals and O2•− radicals were main active species that drive the photocatalytic decolorization of CR solution by m-Fe3O4/BiOBr MSs. Furthermore, the m-Fe3O4/BiOBr MSs can be easily recovered and recycled after the treatment process because of the presence of magnetic Fe3O4. This work suggests that m-Fe3O4/BiOBr MSs may be a promising photocatalyst for photocatalytic treatment of organic wastewater and other environmental remediation.
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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".