Magnetic Nanocomposites: Preparation and Characterization of Polymer-Coated Iron Nanoparticles
Bibliographic record
Abstract
Nanoparticles bearing a strongly bound polymer coating were formed by the thermal decomposition of iron pentacarbonyl in the presence of ammonia and polymeric dispersants. The dispersants consist of polyisobutylene, polyethylene, or polystyrene chains functionalized with tetraethylenepentamine, a short polyethyleneimine chain. Polystyrene-based dispersants were prepared with both graft and block copolymer architectures. Inorganic−organic core−shell nanoparticles were formed with all three types of dispersants. In addition, more complex particles were observed in the case of the polystyrene-based dispersants in 1-methylnaphthalene. The core material was identified as metallic iron, while the particle shells are formed from the polymeric dispersant which binds to the core. High-resolution TEM revealed evidence for crystallization within the polymer shell, possibly facilitated by chain alignment upon binding. The nanocomposites display room-temperature magnetic behavior ranging from superparamagnetic to ferromagnetic. The saturation magnetization and coercivity were found to depend on the diameter of the iron core.
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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".