A novel synthesis method of magnetic Janus particles for wastewater applications
Bibliographic record
Abstract
HYPOTHESIS: Magnetic particles are widely used in many adsorption and removal processes. Among the many types of magnetic colloids, magnetic Janus particles offer significant possibilities for the effective removal of several components from aqueous solutions. Nevertheless, the synthesis of structures integrating different types of materials requires scalable fabrication processes to overcome the limitations of the available methodologies. Herein, we hypothesized a fabrication process for dual-surface functionalized magnetic Janus particles. EXPERIMENTS: The primary silica particles with surface-attached amine groups are further asymmetrically modified by iron oxide nanoparticles, exploiting Pickering emulsion and electroless deposition techniques. The dual surface functionality of the particles is designed for its versatility and demonstrated in two wastewater-related applications. FINDINGS: We show that our design can simultaneously remove chromium (VI) and phenol from aqueous solution. The fabricated magnetic-responsive Janus particles are also an effective adsorbent for genomic Deoxyribonucleic acid (DNA) and show superior performance to commercial magnetic beads. Thus, this study provides a novel platform for designing magnetic Janus particles with multifunctional surfaces for wastewater treatment applications.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".