Formation Features of Hybrid Magnetic Materials Based on Polyphenoxazine and Magnetite Nanoparticles
Bibliographic record
Abstract
Hybrid metal-polymer nanocomposite materials based on polyphenoxazine (PPhOA) and Fe3O4 nanoparticles were obtained for the first time via two methods: in situ oxidative polymerization of phenoxazine (PhOA) in an aqueous solution of isopropyl alcohol with nanoparticles of Fe3O4 being present; chemical transformations of PPhOA subjected to IR heating at 400–450 °С in the presence of FeCl3·6H2O in an inert atmosphere. Obtained hybrid Fe3O4/PPhOA nanomaterials were characterized by means of Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), atomic absorption spectrometry (ААS), elemental analysis, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), as well as by vibrating sample magnetometry. The chemical structure, phase composition, magnetic and thermal properties of obtained nanocomposites were investigated in relation to the synthesis conditions.
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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".