SYNTHESIS AND CHARACTERIZATION OF POLYSTYRENE COATED FUNCTIONALIZED γ -Fe2O3 NANOPARTICLES
Bibliographic record
Abstract
γ-Fe2O3 nanoparticles showing supermagnetic behaviour have been widely studied in recent years for various applications. Polymer coated functionalized γ-Fe2O3 nanoparticles have wide applications which attracted many researchers to study their different nature when they are supported with polymers. Functionalized γ-Fe2O3 nanoparticles has many applications in medical field such as MRI contrast, drug delivery, hyperthermia, magnetic gels, in cancer treatment and also used in memory devices, supermagnetic materials etc. In the present study we synthesized the polystyrene coated functionalized γ-Fe2O3 nanoparticles (PSCFNPs) in the weight ratio through grafting onto method. These nanoparticles were characterized and studied its magnetic property employing B-H loop tracer, molecular structure through FT-IR spectroscopy, thermal study employing TGA, DSC and morphology through Scanning Electron Microscopy (SEM) & transmission electron microscopy (TEM) techniques. Through the mentioned characterization techniques we obtained the formation of fine polystyrene coated functionalized γ-Fe2O3 nanoparticles. The medical applications of the nanoparticles with tailored surfaces by biocompatible polymers are envisioned.
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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".