## 3 Results and Discussion  
The XRD diffractogram of the prepared mixture is given in Figure 3. The analysis of this diffractogram shows that the measured powder's mixture is formed of two phases; the first phase is constituted of hexagonal graphite (it has the same crystalline structure as the graphene), with a space group P63/mmc (Reference pattern PDF2: 00-012-0212), while the second phase is formed of monoclinic crystals of copper oxide, with a space group C2/c (Reference pattern PDF2: 00-045-0937) [39]. It is important to remark the presence of the peaks relative to the reflection (002), at 20 equal to 26.5\({}^{\circ}\) and 35.5\({}^{\circ}\). These two characteristic peaks are assigned to graphite and copper oxide, respectively. The full width at half maximum (FWHM) of diffraction peaks are narrow, indicating the high crystallinity of the prepared mixture. The mixture crystallite size was evaluated using the Scherrer formula:  
\[Crystallite\;size\;(L)=\frac{K\cdot\lambda\cdot cos\theta}{w} \tag{8}\]  
Figure 3: XRD diffractogram of the powder mixture. \(K\) is the shape factor (\(K\) = 0.94) and \(\lambda\) = 1.54178 A. The unit of \(W\) and \(\theta\) should be converted into radian (rad) before using them in the Scherrer formula. The calculated crystallite sizes using the different peak positions are shown in Table 1. The calculated average crystallite size is equal to 18.9 nm. TEM image of CuO-Graphene nanoparticles is described in Figure 4. It is clear from the indicated scale that the nanometric size is well achieved without any agglomeration with uniform nanoparticles dispersion. The impact of varying hybrid nanoparticles mass fraction and temperature on the thermal conductivity is illustrated in Figure 5. As it can be seen, the thermal conductivity is augmented with the increase in either of these two parameters and of both simultaneously. This trend can be explained by the accompanied increase in the kinetic energy of hybrid nanoparticles molecules, which in turn leads to the increase of Brownian motion and promotes nanoparticles interactions. Moreover, by increasing of dispersed nanoparticles mass fraction, their clustering and random collisions increase resulting in an increase in the hybrid nanofluid thermal conductivity. The latter increase is more pronounced for high mass fractions. In fact, for the base fluid (wt% = 0), the maximum thermal conductivity enhancement is nearly 8.2% (from 0.61 at 25 \({}^{\circ}\)C to 0.66 at 60 \({}^{\circ}\)C) whereas for the highest mass fraction (wt% = 1), it is about 24% (from 0.76 at 25 \({}^{\circ}\)C to 0.94 at 60 \({}^{\circ}\)C). The enhancement of the thermal conductivity becomes more important at higher mass fraction, due to the increase in nanoparticles Brownian motions \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline Peak Position, 20 (\({}^{\circ}\)) & 26.5 & 32.5 & 35.5 & 38.7 & 48.7 & 53.4 & 58.3 & 61.5 & 66.1 & 68.0 & 72.4 & 75.1 \\ \hline Crystallite size, L (nm) & 20.2 & 28.2 & 24.1 & 18.4 & 20.0 & 17.5 & 14.8 & 16.8 & 9.4 & 15.8 & 24.4 & 16.7 \\ \hline \end{tabular}
\end{table} 
Table 1: Calculated crystallite sizes using the different peak positions. Figure 4: TEM image of CuO-Graphene nanoparticles. Figure 6 shows the variations of the nanofluid viscosity with temperature and hybrid nanoparticles mass fraction. Obviously, the increase in temperature leads to the decrease in viscosity while the increase of nanoparticles mass fraction enhances the nanofluid viscosity. This trend can be attributed to the decrease in intermolecular cohesion and nanoparticles adhesion forces due to the temperature rise. However, the increment of dispersed nanoparticles loading results in shear stress augmentation and, thus, the increase in viscosity which is not desirable because it enhances the pressure loss in the heat exchanger coils.