Mill Scales Blended Polymer Composites For Electrical Insulation Application
Bibliographic record
Abstract
Standalone composite films were prepared using modified polyester as a binder and waste iron oxides (mill scales) collected from a steel plant as inorganic filler. The morphology, structure, composition, strength and electrical insulation properties of polymer-iron composites were studied using various analytical techniques such as X-ray diffraction (XRD), Scanning electron microscope (SEM), Atomic force microscopy (AFM), optical microscopy, Fourier transform infrared (FTIR) spectroscopy, X-ray fluorescence (XRF), Brunauer–Emmett–Teller (BET) test, particle size analysis and electrical insulation test. The mill scales collected from the hot strip rolling mill (HSM) have found to comprise three different phases such as wustite, magnetite and hematite. Composites prepared using mill scales were showing three times higher strength compared to the mother polymer film. Electrical insulation of these composites were found to increase in the range of 55-230 MV/mm with increasing iron oxide content from 0.0125 g to 0.25 g in 2.5 g polymer. These results show a potential research field on the mill scales based composites for various advanced applications in improving insulation behaviour of materials which can withstand at higher temperatures and electrical stresses.
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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) | 0.002 | 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".