Experimental investigation of nanofluids for heat pipes used in solar photovoltaic panels

Abstract

Keywords: Nanoparticle; Nanofluid; Thermal Conductivity; Density; Therminol-55

Introduction

The world currently consumes around 4.1×1020 joules of energy per year, which is comparable to the continuous power consumption of 13 trillion watts (1). By 2050, global energy demand is expected to rise by 50%, and by the end of the century, it will be more than triple (2). Due to the detrimental impacts of fossil fuels, clean sustainable and alternative sources of energy are required to meet the demand. Solar energy is the primary source of clean and abundant energy for human progress and life on earth. Solar energy can be used to generate electricity either directly through solar photovoltaic (PV) modules or indirectly through thermal power plants. Solar photovoltaic technology is one of the renewable energy alternatives that has the potential to produce a cleaner, scalable, reliable and cost-effective electricity for the future. However, only around 15% of solar radiation is converted to electricity in a PV panel, with the rest converted to heat (1). When the working temperature of the PV module rises, the electrical efficiency decreases. As a result, decreasing the temperature of the PV module can improve its electrical efficiency. With the continous progress in efficient energy systems, the need for design and fabrication of the efficient cooling system is indispensable (3,4). Heat pipes are widely used as a novel cooling technique or as heat recovering systems. Heat pipes find numerous applications such as in solar energy, geothermal systems, space applications, telecommunications and electronic components etc (5–8). For these applications, light weight, small size and high performance are prerequisites for the current heat pipe design, especially for electronic systems (9). Heat pipe is an emerging passive heat transfer device that dissipates heat through phase-change mechanism. Heat pipe utilizes latent heat of vaporization of working fluid to transport heat from source to sink. Since heat pipes transfer heat through evaporation and condensation of working medium, the selection of working medium with improved thermo-physical properties is the key parameter for the efficient design and performanace of heat pipe (4,5). The knowledge and understanding of thermal characteristic of working fluid are important for the design of heat pipes in various applications. Over the years, several techniques have been proposed to enhance the heat transfer characteristics. One of the recent attractive improvements in heat pipe working fluids is the use of nanofluids for achieving higher thermal efficiencies (10–12) In recent years, metal and metal oxide nanoparticles have drawn vast attention due to their novel thermo-physical properties (13,14). With the requirment of further improvement in the performance of the present thermal systems, need for the next-generation fluids is expected. Nano technology has offered a new solution by introducing highly efficient heat transfer fluids with improved thermophysical properties. These highly efficient heat transfer

fluids are known as Nanofluids, a term first proposed by Choi (15). Nanofluids are prepared by mixing nanometersized particles, with dimensions of less than 100 nm containing metals, carbides, oxides or carbon nanotubes in a conventional liquid such as water, acetone, oil and ethylene glycol (EG) etc. These colloidal suspensions of nanosized particles can significantly improve the transport and thermal propeties of the base fluid. Nano-fluid technology has advanced significantly in recent decades and proved its essential applications in cooling of electronic applications, petroleum industries, solar water heating, domestic refrigerator-freezers and in nuclear reactor etc. The main objective of using nanofluids is to exhibit high thermal conductivity at the most appropriate concentration ratio of nanoparticles. Nanofluids have been extensively used as heat transfer fluid (HTF) in engineering applications. Numerous authors have performed experimental and numerical investigations to demonstrate the impact of varying temperature and particle loading range on improvement in thermal conductivity of various nanofluids. Muraleedharan et al. (16) reported the thermal conductivity study of Al2O3/Therminol-55 as the function of nanoparticle concentration (0.025-0.3 vol%). Results show that the thermal conductivity was enhanced by 11.7% for

Materials and Methods

Three different commercially available nanopowders TiO2, ZnO and CuO (procured from Nanoshel, USA) were selected for this study. Lattice parameters were ­calculated from X-ray diffraction (XRD) data of crystal structure. These were suspended in Therminol-55 by twostep method. Therminol-55, used as base fluid, is a high temperature synthetic heat transfer fluid, which offers beneficial thermal features such as high boiling point and reasonably high viscosity at normal temperature (31–33). The various properties of nanoparticles and base fluid are given in Table 1 & 2. For TiO2 nanoparticles lattice parameters were found to be a = b = 3.7830 Å, c = 9.5024 Å and α = β = γ = 90°. For ZnO, lattice constants a = b = 3.24764 Å and c = 5.2027 Å and α = β = 90° and γ = 120°. Similarly, for CuO, lattice parameters a = 4.6884 Å, b = 3.4275 Å and c = 5.1234 Å and α = γ = 90° and β = 99.508°. The average crystallite size of TiO2, ZnO and CuO nanoparticles can be estimated by using Debye Scherer equation. D = Kλ /βCosθ

where, D is the particle diameter size, K is 0.9 (Scherer’s Constant), λ is the wavelength of the X-rays (λ=1.541858Å), β is the full width at half maximum (FWHM) of the diffraction peak and θ is the Bragg diffraction angle.

Preparation of nanofluids Three different nanofluids TiO2/Therminol-55, ZnO/ Therminol-55 and CuO/Therminol-55 have been prepared for varying particle concentrations of 0.05%, 0.075%, 0.1%, 0.5%, 1% and 1.5 wt% using two-step method. In the twostep method, nanoparticles are produced separately and suspended in a base fluid. A sample of 50 ml has been prepared for each experiment. The amount of nanoparticles to be mixed in the base fluid for different particle concentrations is calculated by Equation 2 (34).  Wnp    ρ   np  %ϕ =    Wnp + Wbf  ρ ρbf   np

where, φ is the particle concentration, wnp and wbf represent the weight of nanoparticle and base fluid (grams), ρnp and ρbf represent the density of nanoparticle and base fluid (kg/m3) respectively. Nanofluid stability is significantly important in order to produce a stable suspension to overcome agglomeration and sedimentation of particles. Oleic acid is used as dispersant with an aim of creating more stable nanofluids

as well as to maintain their thermo-physical properties for a long period of time. Oleic acid is used as dispersant, as it is highly miscible and has a viscosity comparable with Therminol-55 (35). Three different mono samples were fabricated with Oleic acid content of 0.5 ml per grams of nanoparticles (16,33). In order to reach uniform distribution of nanometersized particles in the base fluid, each sample with the calculated quantity of nanoparticle concentration of 0.05, 0.075, 0.1, 0.5,1 and 1.5% is added to the mixture of base fluid and the surfactant and then the mixture is stirred with a magnetic stirrer for 3 hours. Next the mixtures of TiO2/ Therminol-55, ZnO/Therminol-55 and CuO/Therminol-55 have been sonicated at 20 kHz frequency for 4, 5 and 6 hours (32,36,37) respectively using a 120W ultrasonic device to break down the agglomeration between the nanoparticles. No sedimentation or precipitation is observed for a long time before the experiments. The resulting nanofluids exhibit uniform dispersion and are stable. The schematic of the experimental procedure used for preparation of nanofluids with varying concentration is shown in Figure 1. Instrumentation for characterization of nanoparticles The morphological characterization of the nanoparticles was conducted by using Transmission Electron Microscope

Figure 1. Schematic of the experimental procedure adopted for preparation of nanofluids.

(TEM) Jeol/JEM-1400 with a maximum accelerating voltage of 120 kV. The crystal structure and crystalline phases of nanoparticles were determined by X-ray diffraction (XRD) using a Rigaku diffractometer equipped with Cu Kα radiation (λ=1.541858Å) within the range of 2 theta 5° to 90°. Fourier Transform Infra-Red (FTIR) spectral measurements were obtained to identify the presence of various functional groups within the compound. The FTIR spectra were collected and studied using (CARY 630, Agilent Technologies, USA) in the wavelength range of 600-4000 cm-1. Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC) is an effective tool to study the thermal behaviour of nanoparticles and its stability. TGA and DSC was conducted using Mettler Toledo TGA/ DSC 3+/HT with alumina crucible.

0-3g/cm3 with the precision of ±0.001g/cm3. These density meters are based on the oscillating U-tube principle. The sample is injected with the help of a syringe through a filling nozzle into the measuring cell. A minimum of 1.5 ml of sample is required. All data was recorded for three times and an average value has been taken for the analysis.

Results & Discussion

Characterization of nanoparticles Characterization of nanoparticles using TEM Figures 2 show the typical transmission electron microscope images (Scale bar = 100 nm) of TiO2, ZnO and CuO nanoparticles respectively. As shown in the Figure, the

Stability analysis of nanofluids using zeta potential The stability of nanofluids is critical in order to maintain its thermo-physical properties for a long period of time. Nanofluids tend to agglomerate due to interactive forces, leading to formation of large clusters that settle rapidly and hence deteriorates the dispersion stability of nanofluids. To improve the stability of colloidal suspensions surfactants or dispersants are generally used. In the present study, Oleic acid is used as surfactant, which lowers the interactive forces between the particles themselves and between the particles and surrounding liquids (38). This phenomenon increases the immersion of particles and can prevent particle aggregation and ensure prolonged stability of nanofluids. The stability of suspensions was determined by measuring zeta potential for each sample by using AntonPaar Litesizer 500. Measurement of thermo-physical properties Thermal conductivity measurement A KD2 Pro thermal property analyzer (Decagon Devices, Inc., USA), uses transient hot-wire method for thermal conductivity data measurement of nanofluids at a temperature ranging from 10°C-90°C with varying solid concentration of 0.05-1.5 wt%. The instrument mainly operates using a transient line heat source technique to measure the thermal conductivity of a liquid medium. The device consists of a handheld controller and a stainless steel 60 mm long KS-1sensor, with 1.3 mm diameter. For precise measurement, the sensor was vertically immersed into the sample to eliminate forced convection. To avoid experimental error, three set of measurements were conducted on each sample and their average values were recorded. Density and surface tension The density was measured by using a portable density meter (Anton Paar, DMA 4500M). The density of nanofluids was measured at the temperature varying from 10°C to 90°C and with varying concentration of 0.05wt% to 1.5wt%. This device can measure the density within the range of

Figure 2. Typical TEM images of (a) TiO2 (b) ZnO (c) CuO nanoparticles.

Figure 3. X-ray diffraction patterns of three different nanoparticles.

morphology of TiO2 and ZnO nanoparticles is approximately spherical whereas that of CuO is in the form of flakes. Characterization of nanoparticles using X-ray diffraction (XRD) Figure 3 shows the X-ray diffraction (XRD) patterns for TiO2, ZnO and CuO nanoparticles. XRD pattern of TiO2 nanoparticles indicate anatase structure as indicated by the strong peaks with reflection planes at 25.32° (101), 37.83° (004), 48.08° (200), 53.97° (105), 55.11° (211), 62.86° (213), 68.87° (116), 70.36° (220), 75.18° (215) and 82.88° (303). The prominent peaks are in good agreement with the reference patterns reported by the JCPDS Card No.00-064-0863. ZnO exhibit hexagonal wurtzite structure as indicated by the broad peaks having 2 theta values with reflection planes at 31.75° (100), 34.47° (002), 36.25° (101), 47.56° (102), 56.63° (110), 62.9° (103), 66.45° (200), 68.01° (112),

69.13° (201) ,72.65° (004), 77.05° (202), 81.26° (104) and 89.74° (203) corresponds to JCPDS Card No.01-080-3030. CuO nanoparticles possess monoclinic phase. The peaks at 32.52° (110), 35.53° (002), 38.77° (111), 46.29° (112), 48.77° (20-2), 53.55° (020), 58.34° (202), 61.58° (11-3), 66.27° (022), 68.14° (113), 72.52° (311), 75.20° (004), 80.26° (023) and 83.1° (31-3) correspond to CuO diffraction peak. The obtained peaks are in good accord with those in the JCPDS card (Card No.01-080-1917). The average crystallite size of the TiO2, ZnO and CuO nanoparticles calculated using Debye Scherer formula was about 16.9 nm, 18.7nm and 16.12nm respectively. Characterization of nanoparticles using Fourier transform infra-red spectroscopy (FTIR) Figure 4 shows the FTIR spectra of TiO2, ZnO and CuO nanoparticles. Metal oxides generally give absorption bands in fingerprint regions below 1000cm-1 emerging

Figure 5. TGA-DTGA curves of (a) TiO2 (b) ZnO (c) CuO nanoparticles.

Table 3. Mass loss (%) at different stages of degradation Sample

Figure 6. Differential scanning calorimetry curves of three different nanoparticles.

from interatomic vibration (39). For TiO2 nanoparticle, the absorbance bands observed between 3500-3000 cm-1 are attributed to hydroxyl (O-H) stretching (40). Peaks at 2923 cm-1 and 2853 cm-1 corresponds to the C-H stretching vibrations (41). Peak at 1640 cm-1 corresponds to C=O vibrations (39–41). For ZnO nanoparticle, the peaks arising between 35393081 cm-1 and 981-875 cm-1 are assigned to O-H and C-N stretching (40,42). Peaks at 2923 are due to sp3 C-H stretching vibrations (43). Peaks present in the region 656-500 are the characteristic absorption peaks of ZnO stretching vibration frequency (44). In the FTIR spectrum of CuO nanoparticles, the peak at 1640 indicates C=C stretching and 1449 indicates aromatic ring stretching (45). Peaks present in the region 660-600 indicate stretching vibrations of Cu-O bond (46). Characterization of nanoparticles using thermogravimetric analysis (TGA) and DTGA The thermal behavior and stability of TiO2, ZnO and CuO nanoparticles was analyzed by using TGA and DSC techniques over the temperature range of 30-700°C under

a uniform heating rate of 10°C min-1. (TGA) and (DTGA) of the three different nanoparticles are shown in Figure 5. The TGA curves in the above Figures clearly indicate that the weight loss of the given nanoparticles is the function of temperature. DTGA curves are calculated as the temperature derivative of the remaining mass percentage from the TGA analysis. TGA curves display three main stages of mass loss. Table 3 and Figure 5 shows that the first stage of decomposition of the nanoparticles start from a temperature range of 23-139°C for TiO2, 22-183°C for ZnO nanoparticles and 23-205°C for CuO. The mass loss of the samples for the TiO2 nanoparticles is up to 1.91%, 1.61% for ZnO and 1.17% for CuO nanoparticles. The mass loss in first stage originates mainly due to release of absorbed water (47). The second stage of degradation occurs in the temperature range of 139-332°C for TiO2, 221-517°C for ZnO and 205-419°C for CuO nanoparticles which is attributed to the evaporation and dehydration of absorbed free and coordinated water molecules from the nanoparticle samples. The second stage shows the mass loss of 0.32% for TiO2, 1.85% for ZnO and 0.69% for CuO nanoparticles respectively. The third stage of degradation shows negligible mass loss. From the curves it is evident that at higher temperatures, no further significant mass loss was observed. There is less percentage drop in mass loss i.e. 0.006% for TiO2, 0.438% for ZnO and 0.586% for CuO nanoparticles. It has been observed from the above TGA and DTGA curves that TiO2 losses less mass than the ZnO and CuO nanoparticles at each stage of decomposition. Hence it is more thermally stable as compared to the other two samples. The major DTGA peaks reach the temperature about 43°C for TiO2, 249°C, 603°C for ZnO and 247°C, 648°C for CuO nanoparticles. Characterization of nanoparticles using differential scanning calorimetry (DSC) DSC is a thermal analytical technique that measures the heat flow in and out associated with sample as a function of temperature. The DSC curve for three different samples is shown in Figure 6. The endothermic process starts from 130°C to 270°C. The DSC curve of TiO2, ZnO and CuO

show the presence of a common wide endothermic peaks 219°C, 230°C and 193°C respectively. Nanofluids stability Zeta potential analysis is an efficient approach to characterize the stability of suspensions quantitatively. Two tests were performed on each sample immediately after 2 hour and on 08th day of the sample preparation. Figure 7 indicates variation in zeta potential for varying particle concentrations of TiO2, ZnO and CuO in Therminol-55 on the 08th day of sample preparation. It is observed that the dispersion stability is maximum for nanoparticle concentration of 0.05 wt% for all three different nanofluids. The stability was observed to decrease with increase in particle concentration. In terms of stability, zeta potential of > ±30 mV are regarded to be stable (38,48,49). For TiO2/Therminol-55, ZnO Therminol-55 and CuO/Therminol-55 nanofluids the measured zeta potential varies from 56.7 to 43.1 mV, 53.2 to 37.5 mV and 49.2 to 30.1 mV with varying particle concentration of 0.05 wt% to 1.5 wt% respectively. Almost all the samples exhibit zeta potential above stability criterion. Visual inspection of all the samples which was done on 8th

Figure 7. Zeta potential of TiO2, ZnO and CuO in Therminol-55 for varying concentration.

day of preparation also confirm the stability as shown in Figure 8.

Thermal Conductivity Measurements

Effect of particle concentration and temperature In this section, the thermal conductivity characteristics of TiO2/Therminol-55, ZnO/Therminol-55 and CuO/ Therminol-55 nanofluids were measured. Assorted parameters that affect the thermal conductivity of nanofluids such as: solid particle concentration, temperature, and thermal conductivity of base fluid as well as that of nanoparticles were analyzed. Thermal conductivity of nanofluids, as a function of temperature (10°C < T< 90°C) and nanoparticle loadings (0.05 < ϕ < 1.5 wt%), were investigated. Most of the experimental studies related to nanofluids focus on determining the role of varying temperature and solid particle concentration on overall enhancement of thermal conductivity (50). The general trend of the experimental results shows that the improvement in thermal conductivity significantly depends on nanoparticle loading and temperature. Further the experimental data obtained have been compared with the existing models to recognize the possible mechanisms responsible for the improvement in thermal conductivity, with increasing particle loading, at higher temperatures. In order to provide a better physical insight, thermal conductivity of pure Therminol-55 was measured over the temperature range of 10°C to 90°C and compared with the literature values. Figure 9 represents variation of thermal conductivity for pure Therminol-55 with temperature. It is apparent from Figure 9 that the thermal conductivity for Therminol-55 decreases with temperature, mainly due to its high viscosity characteristic (35,37). The measured data for temperature dependence of pure Therminol-55 is in good agreement with the data provided by the manufacturers. The effect of TiO2, ZnO and CuO nanoparticle concentration from (0.05 wt% to 1.5 wt %) on thermal conductivity (knf ) of TiO2/Therminol-55, ZnO/Therminol-55 and

Figure 8. Visual inspection of a) TiO2/Therminol-55, b) ZnO/Therminol-55 and c) CuO/Therminol-55 nanofluids on 8th day of sample preparation.

CuO/Therminol-55 nanofluids at 27°C is shown in Figure 10. It is evident from the Figure 10 that the thermal conductivity of TiO2/Therminol-55, ZnO/Therminol-55 and CuO/Therminol-55 nanofluids increases with nanoparticle concentration. The thermal conductivity enhancement for TiO2, ZnO and CuO suspended in Therminol-55 nanofluids at 27°C shows maximum enhancement of 4.10, 5.11 and 5.68% at particle concentration of 1.5%. Improvement in thermal conductivity is observed with addition of nanoparticles in base fluid, is ascertained to the higher intrinsic heat transfer capacity of TiO2, ZnO and CuO nanoparticles (37,51). At lower particle concentrations, the enhancement in thermal conductivity is less significant due to thermal contact resistance. Thermal conductivity is more distinguished at higher concentrations due to the formation of large particle clusters which further enhances the interactions between the nanoparticles, thereby transporting heat more efficiently (52). At higher concentration, due to the increase in the number of nanometer-sized particles in the base fluid, mean free path of nanoparticles gets reduced, resulting in higher intermolecular collisions and thus enhances the thermal conductivity of nanofluids (53,54). Higher thermal conductivity is obtained from all the samples with increasing particle concentration mainly due to the increase in number of nanoparticles available which results in more particle collisions between them. It should be noted that the excessive increase of solid particle concentration should be avoided to prevent precipitation, sedimentation and formation of particle chains which is not desirable. This is very well supported by the fact that in the experimental investigation particle loading should be limited to below 10 wt% (55). Figure 11a show the variation of thermal conductivity of TiO2/Therminol-55 nanofluid with respect to temperature. Examining the experimental data from Figure 11a, for

Measurement Of Density Of Nanofluids

Effect of particle concentration and temperature on density For a more detailed evaluation of effectiveness of nanofluids, influence of particle concentration and temperature on thermo-physical properties is the most crucial and key parameter for the fluid flow characteristic and system design. For this purpose, the variation of nanofluid density with concentration and temperature has been investigated. The density of base fluid was measured at temperatures varying from 10°C to 90°C and the results were compared with the data in literature presented in Figure 13. An excellent agreement is observed between the current measurements and the data available in literature. The density of Therminol-55 based TiO2 nanofluid at different temperature (10°C-90°C) and particle concentration

(0.05wt%-1.5wt%) are Figure 14a. It shows that the density of nanofluids tends to increase with particle concentration and reduces with increase in temperature. The maximum increase of 938 kg/m3 in density of TiO2/Therminol-55 based nanofluid was found to be at the particle concentration of 1.5wt% and at 10°C. The density for ZnO/Therminol-55 nanofluid at varying particle concentrations with different temperatures illustrated in Figure 14b. It is witnessed that the value of density for ZnO/Therminol-55 nanofluid is higher compared to the base fluid for every particle concentration. The highest value of 946 kg/m3 in density of ZnO/ Therminol-55 nanofluid was observed at the concentration of 1.5wt% and at 10°C. The density of CuO/Therminol-55 nanofluid with different temperatures for the particle concentrations of 0.05wt%-1.5wt% are shown in Figure 14c. It can be seen that, with the addition of nanoparticles in base fluid, density of nanofluid intensifies and this amount decreases with increase in temperature. Maximum value of 960 kg/m3 in density of CuO/Therminol-55 nanofluid was observed at concentration of 1.5wt% at 10°C temperature. This trend is in agreement with the results of Said and Saidur (66) and Elias et.al. (67). At 1.5wt% concentration, density of TiO2/Therminol-55, ZnO/Therminol-55 and CuO/Therminol-55 nanofluids is found to be decreased by 5.65%, 5.33% and 6.04% respectively when the temperature is elevated from 10°C to 90°C. Similarly for base fluid, when the temperature is increased from 10°C to 90°C, density gets reduced by 6.14%. A typical common trend was observed among all the nanofluids. Density of nanofluids increased when the particle concentration increased from 0.05wt% to 1.5wt%. This is due to the higher density of solid nanoparticles added (68) in base fluids. The nanoparticles possess very high density as compared to the base fluid. Therefore, increasing the nanoparticle concentration may result in an elevation in the density of nanofluids. An abrupt increase in the density of nanofluids due to the addition of nanoparticles used in various thermal and heat transfer applications is not desirable and may deteriorate convective heat transfer characteristic (69). As there is not sufficient literature available about the densities of therminol-55 based nanofluids, therefore to validate the measured data, the experimental results were compared with the equation available in literature. Experimental results of the density of nanofluids at 20°C and the densities predicted by the Pak and Cho model are shown in Figure 15. Pak and Cho proposed the equation as: ρnf = (1 − ϕ)ρ f +ϕρ p

Figure 14. Density of (a) TiO2/Therminol-55 (b) ZnO/ Therminol-55 and (c) CuO/Therminol-55 nanofluids as a function of temperature with different particle concentration.

Figure 15 shows the predicted results of Pak and Cho model of nanofluids and experimental data. As shown in the figure, the values of Pak and Cho model is lower as compared to experimental data. The above equation failed to predict the enhancement in density of nanofluids. Thus,

Figure 15. The comparative plots for the experimental density and theoretical model at 20°.

Figure 16. Surface tension of nanofluids with respect to the change in particle concentration.

Table 4. Correlations for density of nanofluids with regression coefficient

CuO/water nanofluids observed that the surface tension steadily decreased up to 2% particle concentration. The surface tension of nanofluids decreased with increasing particle concentration and can be attributed to the combined effect of surfactant and nanoparticles added in the base fluid. Higher the content of surfactant and nanoparticles added greater will be the reduction in surface tension of nanofluids. The decline in surface tension of nanofluids is due to the possible addition of surfactant for the stabilization of the suspension. These surfactants get absorbed on the surface of nanoparticles, and induce an electrostatic repulsive force between the particles, which appreciably decreases the surface tension of nanofluids.

there was a need to develop a new multivariable correlation based on the corresponding experimental data for all the nanofluids as a function of particle concentration and temperature. The results were correlated with the equations and regression coefficients given in the Table 4.

Measurement Of Surface Tension Of Nanofluids

Effect of particle concentration surface tension Figure 16 shows the variation in surface tension with respect to the concentration of nanoparticles added. The surface tension was measured at a temperature of 25°C with varying particle loading of 0.05 wt% to 1.5 wt%. It is evident that with the increase in particle concentration, decrease in surface tension is noted. The trends in surface tension were consistent with the findings of Ranjar et.al. (70) for γ-Al2O3 and MgO nanoparticles added in Tri Ethylene Glycol nanofluid and with the observation of Pantzail et al. (71) for

Conclusions

This study determined the thermo-physical properties such as: thermal conductivity, density and surface tension of TiO2/Therminol-55, ZnO/Therminol-55 and CuO/ Therminol-55 nanofluids as a function of particle concentration and temperature. Stability of nanofluids was achieved by using Oleic acid as dispersant. For structural evaluation of nanoparticles various characterization techniques were used. Based on the current measurements, the following conclusions are summarized: i. Experimental results for thermal conductivity show that both nanoparticle concentration and temperature have pronounced effect on thermal conductivity enhancement. The maximum improvement in thermal conductivity for TiO2/Therminol-55, ZnO/ Therminol-55 and CuO/Therminol-55 nanofluids are reported to be 17.62%, 21.55% and 24.32% for the particle concentration of 1.5 wt%.

ii. The theoretical explanations related to clustering of nanoparticles, molecular collisions and Brownian motion together affirm a considerable contribution on the enhancement of nanofluid thermal conductivity which has been demonstrated in current study. iii. The density of nanofluids increased significantly with increase in particle concentration and decrease dramatically with increase in temperature. Increase in density is due to the higher density of solid nanoparticles added in base fluid. iv. Comparison of the present study with the theoretical models for thermal conductivity and density, shows a significant deviation from the observed results for all the three different mono samples. Thus, new correlations were developed for each nanofluid including the particle concentration and temperature based on the experimental data. v. Experimental results demonstrate that the surface tension of nanofluids decrease with increase in nanoparticle loading. The presence of surfactant and absorption of nanoparticles at interface were identified as mechanisms for reduced surface tension of nanofluids. vi. For further heat transfer characteristics, investigation of other thermo-physical properties such as viscosity and specific heat and development of new correlations can be a future part of this work.

Nomenclature

EG Ethylene Glycol HTF Heat Transfer Fluid TiO2 Titanium oxide ZnO Zinc oxide CuO Copper oxide MWCNT Multi wall carbon nanotube DWCNT Double walled carbon nanotube JCPDS  Joint committee on powder diffraction standards Al2O3 Aluminum oxide MgO Magnesium oxide CNT Carbon nanotube Bi2O3 Bismuth oxide Cu Copper XRD X-ray diffraction FWHM Full width half maximum SEM Scanning electron microscope TEM Transmission electron microscope FTIR Fourier transform infra-red TGA Thermogravimetric analysis DTGA Derivative thermogravimetric analysis DSC Differential scanning calorimetry PV Photovoltaic W Weight (gram) k Thermal conductivity (W/mK)

Greek Symbols ϕ Volume fraction λ Wavelength (Angstrom) ρ Density (kg/m3) Subscripts np Nanoparticle nf Nanofluid bf Basefluid

Data Availability Statement

The authors confirm that the data that supports the findings of this study are available within the article. Raw data that support the finding of this study are available from the corresponding author, upon reasonable request.

Conflict Of Interest

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics

There are no ethical issues with the publication of this manuscript.

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