# Smart Nanocomposites for Nanosecond Signal Control: The Nano4 waves Approach
## 3 Results and Discussion
### Electro-Magnetic Characterization of Nano-Inclusions
#### 3.2.2 Magnetic Characterization  
The different types of MNPs considered during this project have as common feature the ferro- (or ferri-) magnetic property. This is of particular interest at microwaves frequencies because of the presence of a so-called ferromagnetic resonance (FMR) occurring in a specific frequency range, which is closely related to both the shape and the magnetic content of the MNPs, namely its saturation magnetization. As will be shown, the detection of the FMR frequency via microwave measurements is an efficient tool for characterizing a number of parameters of ferromagnetic MNPs, in view of the design and fabrication of novel microwave devices for the control of EM propagation. Figure 12 shows an illustrative summary of results obtained for 10 wt.% magnetic Fe\({}_{3}\)O\({}_{4}\) nanoparticles supported on GO. The measurements were performed for several values of DC magnetic field applied perpendicularly to the plane of the substrate (as shown in Figure 4). Figure 12a shows that absorption occurs in the transmitted signal S\({}_{21}\) around a frequency that strongly depends on the value of applied magnetic field. The dependence is strongly linear as predicted by the Kittel theory [24]. Figure 12b shows the extracted values of permeability \(\upmu\) for different values of the DC field. The permeability can thus be tuned by the DC magnetic field, which is relevant for the design of adaptive and reconfigurable devices, in particular for absorbers. Figure 11: (**a**) Comparison of electrical parameters \(\epsilon_{r}\) (**a**) and \(\sigma\) (**b**) for nickel (Ni) and magnetite loaded at 30% on graphene oxide (GO). Figure 12: (**a**) Dependence of FMR phenomenon on applied DC magnetic field ranging from 0 kOe to 7 kOe, for magnetic Fe\({}_{3}\)O\({}_{4}\)@GO nanoparticles (**b**) real (top) and imaginary (bottom) part of permeability \(\upmu_{r}\). FMR characterization can also serve as probing tool for magnetic content, as observed in Figure 13. It shows that the level of signal at FMR resonance is closely related to the loading rate in magnetic nanoparticles. We also demonstrate a strong correlation between the so-called natural frequency, i.e., the measured frequency where FMR resonance is observed at zero DC magnetic field, and the measured saturation magnetization M\({}_{\text{s}}\) of the MNPs depending on their chemical nature. A proportional and linear dependence is observed in Table 3 for different iron-containing MNPs@GO. Polycarbonate films combining NCS and magnetic nanoparticles were also considered. Films characterized in Figure 14 were prepared by mixing them in a twin co-rotating extruder and compression-molding, as described in Section 2.3. In all samples, a ferromagnetic resonance (FMR) response was observed (Figure 14a). More interestingly, samples containing the same magnetite loading and increasing GNPs content showed a significant increment of absorption, which was unexpected since graphene is not magnetic in nature. As a result, a synergy between the two components was concluded. This was further corroborated by the TEM micrographs (Figure 14b) and size distribution analysis based on TEM micrographs (Figure 14d-f) that show, for the same loading of magnetite, reduced size of magnetite nano-agglomerates with increasing GNPs concentration. The presence of high GNPs loading has the effect of increasing hydrodynamic forces during the extrusion process, which results in the breakage of larger agglomerates into smaller ones. The SQUID measurement shown in Figure 14c reveals that smaller agglomerates obtained with GNPs/MNPs mixing have a higher saturation magnetization, explaining the increase of absorption in the presence of GNPs. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Alloy** & **Fe\({}_{3}\)O\({}_{4}\)** & **FeNi** & **FeCoNi** & **FeCo** \\ \hline Natural FMR (GHz) & 2.1 & 3.9 & 6.3 & 8.6 \\ \hline \(M_{\text{s}}\) (emu/g) & 61 & 124 & 187 & 205 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Dependence of FMR on M\({}_{\text{s}}\) for various alloys.