Enhancing absorption dominated microwave shielding in Co@C–PVDF nanocomposites through improved magnetization and graphitization of the Co@C-nanoparticles
Why this work is in the frame
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Bibliographic record
Abstract
Using composites of polyvinylidene fluoride (PVDF) and carbon nanostructures embedded with Co-nanoparticles we demonstrate that electromagnetic shielding effectiveness depends strongly on the graphitic carbon concentration and the magnetic properties of Co-particles. Cobalt nanoparticles encapsulated by graphitic carbon embedded in an amorphous carbon-matrix were synthesized by a one-pot pyrolysis method at two different synthesis temperatures, TS = 800 °C (Co-800) and 1000 °C (Co-1000). We demonstrate that TS plays an important role in determining the structure, morphology and magnetic properties of the carbonaceous matrix, the graphite layer and the Co nanoparticles. Higher amounts of graphitic carbon and high saturation magnetization were observed for the Co-1000 sample than that for the Co-800 sample. We observed that the electromagnetic interference (EMI) shielding behavior of the PVDF-Co-1000 nanocomposite shows higher shielding effectiveness than that of the PVDF-Co-800 specimen. A more inhomogeneous dielectric medium in the PVDF-Co-1000 composite results in higher dielectric loss and impedance mismatch. A direct correlation between the shielding effectiveness with dielectric permittivity and magnetic permeability is demonstrated. The synergy between the multiple reflections at the interfaces and absorption of the microwave radiation in the conducting species confirms that a higher degree of graphitization and highly magnetic particles in nanocomposites are effectively superior for EMI shielding of microwave radiation.
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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 | 0.000 | 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) | 0.000 | 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 it