**3. Results and Discussion**

*3.1. Characterization of Nanofluids*

SEM procedures are used to determine the content of particles based on the spectrum of the transmitted beam from the samples; they allow the size of irregularly sized particles or impurities to be determined. Moreover, SEM helps determine the distribution of nanoscale particles onto the surface of any sample. Figure 3a displays the SEM micrograph of the prepared PEG@GNPs; it is evident that the PEG@GNPs included several differentsized GNP-flakes, implying the samples' high-purity level. Examination via the electron beam demonstrated that most flakes were transparent due to the limited number of their layers, though difficulties in determining precise flakes and defects diameter through SEM

manifested themselves in sharper planar morphology of the GNP layers on the obtained SEM micrographs. Figure 3b displays the high-resolution SEM image of the PEG@TGr prior to any kind of pre-treatment. Also, consistency and intactness of the grains, curves, and wrinkling were observed on some of the transparent SEM images because of the strict production process. The existence of new functional groups in the PEG@TGr was revealed in observed functionalization-induced wrinkles in the images. *Nanomaterials* **2022**, *12*, x FOR PEER REVIEW 8 of 21

**Figure 3.** Visualization of different SEM nanoparticles; (**a**) Graphene nanoplatelets, (**b**) Graphene, (**c**) Alumina, (**d**) Silica. **Figure 3.** Visualization of different SEM nanoparticles; (**a**) Graphene nanoplatelets, (**b**) Graphene, (**c**) Alumina, (**d**) Silica.

Figure 3c introduces the SEM image of the 0.1 wt.%-Al2O3@DW nanofluid; the image illustrates rod-like and rectangular-shaped alumina nanoparticles with a low tendency towards agglomeration of the excellence of the prepared suspension. Furthermore, the image demonstrated exceptional dispersal of the sample after 60 min of ultrasonication. Additionally, the nanoparticles demonstrated a homogeneous grain size (<50 nm), suggesting the prepared nanoparticles were spherical and showed a treatment-dependent size distribution. In the current study, it was observed from Figure 3c that the major bulk of the sample was Al2O3. This confirms the high purity of the sample and the suitability of the applied synthesizing methodology. Furthermore, Figure 3d shows the SEM image of 0.1 wt.%-SiO2@DW after 60 min ultrasonication nanofluid; the image shows the silica nanoparticles showing rod-to-round-like morphological, but with minor clusters and a better suspension. The size of nanoparticles was also found to be uniform, with <50 nm. Figure 3c introduces the SEM image of the 0.1 wt.%-Al2O3@DW nanofluid; the image illustrates rod-like and rectangular-shaped alumina nanoparticles with a low tendency towards agglomeration of the excellence of the prepared suspension. Furthermore, the image demonstrated exceptional dispersal of the sample after 60 min of ultrasonication. Additionally, the nanoparticles demonstrated a homogeneous grain size (<50 nm), suggesting the prepared nanoparticles were spherical and showed a treatment-dependent size distribution. In the current study, it was observed from Figure 3c that the major bulk of the sample was Al2O3. This confirms the high purity of the sample and the suitability of the applied synthesizing methodology. Furthermore, Figure 3d shows the SEM image of 0.1 wt.%-SiO2@DW after 60 min ultrasonication nanofluid; the image shows the silica nanoparticles showing rod-to-round-like morphological, but with minor clusters and a better suspension. The size of nanoparticles was also found to be uniform, with <50 nm.

Figure 4 shows the EDX analysis for GNPs, Gr, Al2O3, and SiO<sup>2</sup> nanomaterials. As shown in Figure 4a,b, the carbon nanostructures show five elements (C, O, Si, S, and Zr). Figure 4c shows two elements only (Al and O). At the same time, Figure 4d presents three Figure 4 shows the EDX analysis for GNPs, Gr, Al2O3, and SiO<sup>2</sup> nanomaterials. As shown in Figure 4a,b, the carbon nanostructures show five elements (C, O, Si, S, and Zr). Figure 4c shows two elements only (Al and O). At the same time, Figure 4d presents three

different elements (Si, O, and Br). The various elements refer to different synthesizing ap-

proaches used in this study.

different elements (Si, O, and Br). The various elements refer to different synthesizing approaches used in this study. *Nanomaterials* **2022**, *12*, x FOR PEER REVIEW 9 of 21

**Figure 4.** EDX images of different nanoparticles; (**a**) Graphene nanoplatelets, (**b**) Graphene, (**c**) Alumina, (**d**) Silica. **Figure 4.** EDX images of different nanoparticles; (**a**) Graphene nanoplatelets, (**b**) Graphene, (**c**) Alumina, (**d**) Silica.

#### *3.2. Thermophysical Properties Measurements 3.2. Thermophysical Properties Measurements*

In comparison to distilled water, different nanofluids were described from the perspective of thermophysical properties as a function of mass fractions and temperature, as illustrated in Figure 5. The thermal conductivity of the working fluids plays a critical role in increasing heat removal efficiency from the heat exchangers to the environment. Current findings closely followed existing correlations offered by the National Institute of Science and Technology (NIST) [36], with a maximum standard error of 2%. As shown in Figure 5a, the nanofluids showed considerably higher thermal conductivity than DW; increases in temperature also rose thermal conductivity. The nano-coolants demonstrated a perfect, effective thermal conductivity increase rate at higher mass percentages. The temperature improved thermal conductivity significantly as a result of the increase in the nanoparticles' Brownian motion upon DW. The increases in thermal conductivity were for PEG@GNP =31.6%, PEG@TGr= 29.74%, SiO<sup>2</sup> =11.4%, and Al2O<sup>3</sup> = 8.04% at 0.1 wt.% and 60 °C. Table 2 summarizes the thermal conductivity study by the previous investigators. In comparison to distilled water, different nanofluids were described from the perspective of thermophysical properties as a function of mass fractions and temperature, as illustrated in Figure 5. The thermal conductivity of the working fluids plays a critical role in increasing heat removal efficiency from the heat exchangers to the environment. Current findings closely followed existing correlations offered by the National Institute of Science and Technology (NIST) [36], with a maximum standard error of 2%. As shown in Figure 5a, the nanofluids showed considerably higher thermal conductivity than DW; increases in temperature also rose thermal conductivity. The nano-coolants demonstrated a perfect, effective thermal conductivity increase rate at higher mass percentages. The temperature improved thermal conductivity significantly as a result of the increase in the nanoparticles' Brownian motion upon DW. The increases in thermal conductivity were for PEG@GNP = 31.6%, PEG@TGr = 29.74%, SiO<sup>2</sup> = 11.4%, and Al2O<sup>3</sup> = 8.04% at 0.1 wt.% and 60 ◦C. Table 2 summarizes the thermal conductivity study by the previous investigators.

Figure 5b compared different nano-coolants and the base fluids in terms of their effective dynamic viscosity at the testing conditions of 0.1 wt.%, the temperature range of 20–60 ◦C, and a shear rate of 200 s−<sup>1</sup> . Figure 5b showed a minor increase in the nanofluids' dynamic viscosity following that for DW, and the main reason for this increase is using low concentrations. It is assumed that fluid viscosity increases can result in pumping fluid penalty in the thermal applications; the nanofluids and DW also exhibited reduced dynamic viscosity due to the intermolecular forces degradation at increased temperatures [37]. The dynamic viscosity of all the samples showed a similar decreasing tendency, but the results evidenced increases in the base fluids' dynamic viscosity. This validates the reliability of the proposed synthesis method for nanofluids in this study. Table 3 summarizes the dynamic viscosity study by previous researchers.

**Figure 5.** The thermophysical properties of base fluid and nanofluids; (**a**) Thermal conductivity, (**b**) Dynamic viscosity, (**c**) Density, (**d**) Specific heat capacity. **Figure 5.** The thermophysical properties of base fluid and nanofluids; (**a**) Thermal conductivity, (**b**) Dynamic viscosity, (**c**) Density, (**d**) Specific heat capacity.

Figure 5b compared different nano-coolants and the base fluids in terms of their effective dynamic viscosity at the testing conditions of 0.1 wt.%, the temperature range of 20–60 °C, and a shear rate of 200 s−1 . Figure 5b showed a minor increase in the nanofluids' dynamic viscosity following that for DW, and the main reason for this increase is using low concentrations. It is assumed that fluid viscosity increases can result in pumping fluid penalty in the thermal applications; the nanofluids and DW also exhibited reduced dynamic viscosity due to the intermolecular forces degradation at increased temperatures [37]. The dynamic viscosity of all the samples showed a similar decreasing tendency, but The density of the different working fluids was tested at a temperature range of 20 to 60 ◦C (see Figure 5c). The data showed a remarkable decrease in density with temperature and a slight increase in density with the nanofluid type. The nanoparticle's density contributed to the improved density of the nano-coolants as it was higher than that of the base fluid. The observed improvement in the nanofluid density was as follows: PEG@GNP = 5.3%, PEG@TGr = 4.5%, Al2O<sup>3</sup> = 2.6%, and SiO<sup>2</sup> = 1.2% for 0.1 wt.% and 60 ◦C. However, the density reduced as follows: PEG@GNP = 1.7%, PEG@TGr = 1.8%, Al2O<sup>3</sup> = 2.1%, and SiO<sup>2</sup> = 2.7% after raising the temperature of the nanofluid from 20 to 60◦C, thereby demonstrating the significant role of temperature.

the results evidenced increases in the base fluids' dynamic viscosity. This validates the reliability of the proposed synthesis method for nanofluids in this study. Table 3 summarizes the dynamic viscosity study by previous researchers. The density of the different working fluids was tested at a temperature range of 20 to 60 °C (see Figure 5c). The data showed a remarkable decrease in density with temperature and a slight increase in density with the nanofluid type. The nanoparticle's density Also, the specific heat capacities are measured in this study (see Figure 5d). The specific heat showed insignificant reductions with temperature increases, but the observed gradient concurred with the specific heat plots reported in the earlier studies [38]. Figure 5d evidenced the average specific heat decreases as follows: PEG@GNP = 5.4%, PEG@TGr = 4.8%, Al2O<sup>3</sup> = 2.9%, and SiO<sup>2</sup> = 1.8% compared to that of DW. This reduction was the lower specific heat of the solid nanoparticles relative to the base fluid.

contributed to the improved density of the nano-coolants as it was higher than that of the base fluid. The observed improvement in the nanofluid density was as follows: PEG@GNP = 5.3%, PEG@TGr = 4.5%, Al2O<sup>3</sup> = 2.6%, and SiO<sup>2</sup> = 1.2% for 0.1 wt.% and 60 °C. However, the density reduced as follows: PEG@GNP = 1.7%, PEG@TGr = 1.8%, Al2O<sup>3</sup> = 2.1%, and


**Table 2.** Summary of thermal conductivity in previous experimental studies.

**Table 3.** Summary of viscosity in previous experimental studies.

