Synthesis and characterization of core-shell Fe3O4-gold-chitosan nanostructure
Bibliographic record
Abstract
BACKGROUND: Fe₃O₄-gold-chitosan core-shell nanostructure can be used in biotechnological and biomedical applications such as magnetic bioseparation, water and wastewater treatment, biodetection and bioimaging, drug delivery, and cancer treatment. RESULTS: Magnetite nanoparticles with an average size of 9.8 nm in diameter were synthesized using the chemical co-precipitation method. A gold-coated Fe₃O₄ monotonous core-shell nanostructure was produced with an average size of 15 nm in diameter by glucose reduction of Au³⁺ which is then stabilized with a chitosan cross linked by formaldehyde. The results of analyses with X-ray diffraction (XRD), Fourier Transformed Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM), and Atomic Force Microscopy (AFM) indicated that the nanoparticles were regularly shaped, and agglomerate-free, with a narrow size distribution. CONCLUSIONS: A rapid, mild method for synthesizing Fe₃O₄-gold nanoparticles using chitosan was investigated. A magnetic core-shell-chitosan nanocomposite, including both the supermagnetic properties of iron oxide and the optical characteristics of colloidal gold nanoparticles, was synthesized.
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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".