Ferrite Nanocomposites: Characteristics of Optical and Microwave Performance
Bibliographic record
Abstract
In this work, we investigated the effect of ferrite addition on two polymers (PEO/PMMA) with different weight percentages (1.2, 2.4, and 3.6 wt%).The solution casting technique was used to fabricate the samples, The nanocomposites were studied to further investigate their composition, structure, and insulating properties (PEO/PMMA-Co-Ni-Cr Fe2O4).Optical micrographs show an additional distribution of nPs, and the mixture was homogeneous; the Co-Ni-Cr Fe2O4 nanoparticles were found in a continuous and ordered structure.Within the lattice, a polymer was present at a concentration of 6 wt%.The spectra exhibited variations in band position and intensity, indicating significant chemical interaction between the polymer and the nanoparticles.Experimental results show that with increasing concentration of (PEO/PMMA-Co-Ni-Cr Fe2O4) nanocomposites, their dielectric loss, insulating constant, and dielectric loss increase, while the ferrite nanomaterial decreases, with increasing electric field repetition rate.On the other hand, the AC electrical conductivity increases.The nanoparticles increase in both frequency and concentration.The (PEO/PMMA-Co-Ni-Cr Fe2O4) nanostructures may be used to develop new nanocomposite films for microwave absorption applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".