Investigation of Fe3O4/Graphene nanohybrid heat ...

International Communications in Heat and Mass Transfer 87 (2017) 30–39

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International Communications in Heat and Mass Transfer journal homepage: www.elsevier.com/locate/ichmt

Investigation of Fe3O4/Graphene nanohybrid heat transfer properties: Experimental approach

MARK

Saeed Askaria, Hadis Koolivanda, Mahnaz Pourkhalila, Roghayyeh Lotfia,b, Alimorad Rashidia,⁎ a b

Nanotechnology Research Center, Research Institute of Petroleum Industry (RIPI), West Blvd. Azadi Sports Complex, P.O. Box 14665, 1998, Tehran, Iran Mechanical Engineering Department, Penn State University, University Park, P.O. Box 16803, State College, USA

A R T I C L E I N F O

A B S T R A C T

Keywords: Nanofluid Fe3O4–Graphene nanohybrid Rheological properties Heat transfer enhancement

In this study, a hybrid of Fe3O4/Graphene was synthesized for nanofluid applications. The synthesized nanohybrid was characterized by X-Ray diffraction (XRD), Transmission electron microscopy (TEM), Zeta potential and Dynamic light scattering (DLS). Stability of the nanofluid was investigated at a wide pH range. Furthermore, rheological properties of the nanofluid including density and viscosity were evaluated. Thermal conductivity of the nanofluid was assessed at 0.1, 0.2 and 1%.Wt loadings of nanohybrid; in comparison to the base fluid 14–32% improvement was observed at 20–40 °C. Density and viscosity measurements of the nanofluid calculations for the base fluid indicated that the experimental data are in good agreement with the theoretical models. The convective heat transfer enhancement of the nanofluid flowing through a straight horizontal tube was investigated experimentally for a Reynolds number range of 2000–5000. In comparison to the base fluid 14.5% enhancement in convective heat transfer coefficient of nanofluid was observed.

1. Introduction These days, heat transfer improvement of base fluids for achieving thermally efficient industrial equipment is a key parameter to conserve energy. Conventional heat transfer fluids such as water, oil and ethylene glycol greatly abide low heat transfer performance in industrial processes. Indeed thermal conductivity of a fluid has an essential role in enhancing heat transfer equipment thermal efficiency [1,2]. By the way compilation in thermal conductivity of conventional heat transfer fluids without any additives reveal that these fluids have an order-of-magnitude smaller thermal conductivity than fluids with metallic or nonmetallic particles. Introducing of solid particles in micrometer sizes was the subject of research works for many years [3]. Due to the large sizes of particles, rapid sedimentation, high pressure drops and damages to the equipment walls, use of such a solid particle for heat transfer enhancement was not practical. In contrast using smaller sizes of particles, i.e., nanoparticles can enhance heat transfer properties of fluids significantly, minimizing the above-mentioned problems of micro particles. Commercial fluids containing nanometer-sized solid particles are termed “nanofluids” [4]. However, one of the main challenges in application of nanofluids in the industry is the stability of nanoparticles in the base fluid. Stability of nanofluids depends on different parameters such as pH, surfactant type and concentration, Vander Waals interactions, nanoparticle concentration, size and shape of particles [5]. Use of

⁎

Corresponding author. E-mail address: [email protected] (A. Rashidi).

http://dx.doi.org/10.1016/j.icheatmasstransfer.2017.06.012

0735-1933/ © 2017 Elsevier Ltd. All rights reserved.

carbon nanomaterials has been the subject of interest because of lower density and higher thermal conductivity of carbon materials compared to other nanoparticles. Carbon nanomaterials such as carbon nanotubes, Graphene, Carbon Nano fibers and Nano Diamond are suitable for application in nanofluids [6,7]. Graphene, which is a new form of carbon Nano materials, has very promising physical, chemical and mechanical properties with two-dimensional honeycomb network of carbon atoms. Different characteristics of Graphene such as high thermal conductivity, prominent mechanical strength, remarkable surface area, and high electrical conductivity have converted Graphene to a superior material for improving physical, chemical and mechanical properties in different applications. Use of Graphene sheets for enhancement of heat transfer properties of base fluids has been studied by many research groups [8–10]. Unfortunately, Graphene in water-based fluids has not good dispersion capability, since the hydrophobic nature of this nanomaterial makes it to agglomerate in water. To reach suitable stability of Graphene nanofluid in water, it is necessary to use methods such as adding surfactants. As mentioned previously such surfactants affect the heat transfer characteristics of nanofluids and may decrease the thermal conductivity of the nanofluid in comparison to the base fluid. On the other hand, coating Graphene Nano Sheets by inorganic materials can be a novel solution to enhance the stability of Graphene nanofluid. Metal and non-metal nanoparticles can make a significant heat transfer improvement in base fluids. Many different research


S. Askari et al.

Nomenclature X Di “q V I L h T Ts Tm p ṁ Cp Nu

K Re Pr F

Entrance length, m inner tube diameter, m Heat flux, W/m2 Voltage, V Current, A Length, m heat transfer coefficient, W/m2.K Temperature, °C wall temperature, °C average temperature of fluid in tube, °C surface perimeter, m mass flow rate, kg/s specific heat, J/kg K Nusselt number

thermal conductivity, W/m.K Reynolds number Prandtl number fraction factor

Greek symbols μ ρ

viscosity, Ns/m2 Density, kg/m3

Subscripts bf nf w

base fluid Nanofluid Wall

nanohybrid has been explained, then nanofluid preparation and stabilization has been discussed. Next, rheological properties of Fe3O4/ Graphene nanofluid including density and viscosity of nanofluid have been assessed and it has been shown that theoretical models can predict the density and viscosity of nanofluid accurately. Finally, thermal properties of Fe3O4/Graphene nanofluid including thermal conductivity and convective heat transfer coefficient have been investigated and then the effect of Fe3O4/Graphene nanohybrid in heat transfer enhancement of base fluid has been evaluated.

works have investigated the effect of nanoparticles such as zinc oxide, magnesium oxide, aluminum oxide, titanium oxide, copper oxide, iron oxide, and etc., as the additives to the fluids for heat transfer enhancement [11–13]. Among them it has been shown that Fe3O4 can improve heat transfer significantly [14,15]. Moreover different advantages including low cost, availability, magnetic properties and environmental friendly nature of Fe3O4 nanoparticles have made this nanoparticle as a promising candidate for future nanofluids application in industry. But again the main challenge in using of these nanoparticles is the stabilization issue of these materials which cannot remain stable by themselves alone in the fluid and as a result of this matter a surfactant is needed as an additive. A hybrid material is a homogenous combination of different materials which benefits the physical and chemical properties of the composing materials simultaneously. Graphene sheets have the capability of forming hybrids with different materials including metal oxide particles [16,17]. Graphene and Graphene hybrids have been applied in different applications such as super capacitors, fuel cells, lithium batteries, sensors, catalysts and etc. [18–20]. For example, Yang et al. used Graphene sheets/Fe2O3 nanorods composite for super capacitors, because of their enhanced electrochemical performance [21]. Fe2O3–CNT– Graphene hybrid material was used for high capacity lithium storage [22]. Furthermore, hybrid of Graphene/metal oxide layers was used for large area organic photovoltaic [23]. Zhu and Dong used Graphene/supported noble metal hybrid nanostructures as advanced electro catalysts for fuel cells [24]. Li et al. studied the effect of surface modification on the stability and thermal conductivity of water-based SiO2-coated Graphene nanofluid [25]. Hybrid of Fe3O4–Graphene has been used for some applications. For instance, Su et al. used hybrid of Graphene and Fe3O4 for drug delivery [26]. Thu et al. used Fe3O4–Graphene nanohybrid for magnetic and conductive membranes [27]. Several studies applied Graphene and CNT metal oxide nanohybrid for improving thermal and thermo physical properties of the fluids, and achieving energy efficient systems [28]. But still the application knowledge of Fe3O4/Graphene hybrid nanomaterials as nanofluids agent has not been developed yet. Embedding metal oxides on Graphene sheets with functional groups, prevents the Graphene agglomeration and eliminates the need of surfactants for nanoparticles stabilization in base fluid. Furthermore use of Graphene/metal oxide hybrid can enhance heat transfer characteristics of the fluid significantly. The reason can be attributed to the fact that both Graphene and metal oxides can improve heat transfer characteristics separately, also the enhancement synergy could be seen when these structures are used simultaneously. In the present work hybrid of Fe3O4/Graphene has been used for application as a water-based nanofluid and in continuation thermal and rheological properties of nanofluid has been investigated. In the first section the synthesis procedure and characterization of the casted

2. Materials and methods 2.1. Chemicals Graphite, Ferrous chloride (FeCl2 · 4H2O), Ferric chloride (FeCl3 · 6H2O), Potassium permanganate (KMnO4), aqueous Ammonia solution(NH4OH 30 % . Wt), Sulfuric acid, Nitric acid, Hydrochloric acid were all purchased from Merck. All materials were used as received without further purification and deionized water was used in all steps of the experimental tests. 2.2. Synthesis of Graphene oxide For synthesis of Graphene oxide, Hummer's method [29,30] was used. At first 1 g of graphite powder was mixed with sulfuric acid and was stirred for 10 min. Then 6 g of potassium permanganate was added to the mixture during 10 min under severe agitation. The mixture was stirred for 24 h in the room temperature for completing the reaction. Then 150 ml water was added to the mixture and after 15 min, 50 ml hydrogen peroxide (18%.Wt) was added to the mixture. After that, the mixture was centrifuged and washed by hydrochloric acid for several times followed by using deionized water for washing the mixture until the neutral pH was reached. Finally 500 ml deionized water was added and sonication, the mixture was centrifuged to separate the unstable part from the stable part. 2.3. Synthesis of Fe3O4/Graphene nanohybrid 99.5 mg of FeCl2.4H2O with 270 mg of FeCl3.6H2O was dissolved in 30 ml deionized water and the mixture was stirred for 5 min. Then 30 ml Graphene oxide (1 mg/ml) was added to the mixture at room temperature. During severe agitation 2 ml ammonia solution was added drop wise for making the color change from light brown to dark brown and finally to black. The mixture was heated to temperature of 80 °C and was kept in this temperature for 1 h by severe agitation. After cooling the mixture to room temperature, the solid material was separated from water by using a magnet. The product was washed by 31


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length and 1.3 mm diameter was used for thermal conductivity measurement. This technique works by measuring the temperature/time response of the probe to an external electric pulse. The amount of sample for thermal conductivity measurement is 30 ml and for each measurement 15 min time is given to the sensor to equilibrate. Constant temperature bath by using a circulator (PolyScience, model 9712, USA) is applied to maintain temperature uniformity within ± 0.1 °C during thermal conductivity measurement.

deionized water several times until the pH of 7 was reached. The formation reaction of Fe3O4/Graphene nanohybrid can be ascribed by Eq. (1). Fig. 1 shows schematic of the synthesis hybrid Fe3O4/Graphene Nano particles.

FeCL 2 + 2FeCL3 + 8NH 4 OH → Fe3 O4 (onGO) + 8NH 4 CL + 4H2 O (1) 2.4. Characterization

2.7. Experimental setup X-ray powder diffraction (XRD) analysis of Fe3O4/Graphene nanohybrid was conducted to identify the crystalline structure of the sample by using X-ray diffractometer (X'Pert MPD model, Philips, Holland) equipped with Cu Kα radiation line. Fourier transform infrared spectroscopy (FTIR spectra PerkinElmer Spectrum GX) was used for analyzing the properties of hybrid nanoparticles. The size and morphology of Fe3O4/Graphene nanohybrid were examined by transmission electron microscopy (TEM), which was carried out using a JEOL JEM2010F microscope operated at an accelerating voltage of 200 kV. For TEM measurements, the Fe3O4/Graphene powder was dispersed in ethanol using ultra sonication and was dropped over carbon coated copper grids.

For investigating convective heat transfer characteristics of nanofluids an experimental setup was developed. As it can be seen in Fig. 2, the setup mainly consists of a horizontal copper tube (test section), a pump, a reservoir tank, a shell and tube heat exchanger and a circulator. The straight copper tube with 10 mm and 10.2 mm inner and outer diameter respectively and with 90 cm length is used as a test section. Because of importance of entrance length and its effect on experimental measurements, 100 mm of entrance length is calculated by Eq. (2) for turbulent regime and applied in current experimental design (Fig. 2) [32]. (2)

X ≥ 10Di

The ultra-high temperature device (Heating tape Omega, USA) used for generating constant heat flux by heating the tube surface, and Variac transformer accompanied a watt/amp meter are used for controlling heating tape performance. A 40 mm thick rock wool is used for insulation of tube surface and preventing heat loss to environment. As illustrated in Fig. 2, K-type thermocouples have been mounted at inlet, outlet and wall of test section used for measuring of temperature. For controlling of fluid quantity in a range of 0.01–0.05 lit/s, the pump (HV-77921-40) has been used. Heat exchange with coolant fluid in shell and tube exchanger helps to keep the inlet line of the test section at the constant temperature. The nanofluid passes through the tubes, while the coolant flows through the shell-side. The coolant fluid then directed into the circulator bath (Poly-Science, model 9712, USA) to maintain its temperature stable by the measured temperatures, the heat flux and nanofluid local heat transfer coefficient is calculated by Eqs. (3) and (4).

2.5. Nanofluid preparation In order to prepare the Fe3O4/Graphene nanofluids, two-step procedure was applied. At first, desired amount of Fe3O4/Graphene nanohybrid was added to base fluid (deionized water), and the solution was placed under ultrasonic disruptor for 10 min using a 130 W, 20 kHz probe (Heilscher, UP400S, Inc., USA) [5,31]. After that the pH of solution was set and the mixture was sonicated for another 10 min. Note that to avoid overheating, ultra sonication was performed intermittently with intervals of 5 s for working time and 5 s for resting time. To check the effect of pH on stability of the nanofluid, eye examination was used to assess the sedimentation of nanomaterials during different time intervals. For examining the stability of nanofluid, zeta potential of the nanofluid was measured by Malvern ZS Nano analyzer (Malvern Instrument Inc., London, UK), moreover particle size distribution (PSD) was measured. The measurement was run at a voltage of 10 V and temperature of 25° C with switch time of 50 s. In order to ensure the accuracy of data, each experiment was repeated for at least 3 times after which the mean value of the data was calculated.

q″ =

VI πDL

(3)

Where V, I, D and L are voltage, electrical current, diameter and tube length, respectively.

2.6. Nanofluid properties

h(x) =

To investigate the performance of Fe3O4/Graphene nanofluid, rheological properties included density and viscosity, thermal characteristics included thermal conductivity and convective heat transfer coefficient of the nanofluid were evaluated. For density measurement, in the present research Pycnometer (ASTM D153) was used. To obtain the density of nanofluids, the Pycnometer was weighted in three cases of being empty, filled by water and filled by nanofluid. For viscosity measurement of opaque liquids, BS/IP/RF U-tube reverse flow capillary viscometer (ASTM D445–06) was used. The viscosity was calculated by measuring the time for a volume of liquid sample (with minimum volume of 7 ml) to flow under gravity through a calibrated capillary space and multiplying the time by the viscometer constant of 0.003. Since temperature has an essential role in viscosity of the fluids, the viscosity of nanofluid was measured at different temperatures. The oil bath with a certain temperature is applied in experiments for minimizing viscosity variation effects, also before measuring the viscosity 20 min waiting time is needed for insuring temperature stability. Thermal conductivity measurement of nanofluid was implemented by transient hot wire method. KD2 Pro thermal property analyzer (Decagon devices, Inc., USA) with probe of 60 mm

q′ ′ Ts (x) − Tm (x)

Fig. 1. Synthesis of hybrid Fe3O4/Graphene.

32

(4)


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Fig. 2. a) Experimental setup for measurement of convective heat transfer coefficient and b) sectional view of the experimental test sections.

In which Tm(x), Ts(x), h(x) and q′′ are the average temperature of nanofluid, the wall temperature, the heat transfer coefficient and the heat flux, respectively. The average temperature of nanofluid can be calculated by Eq. (5)

Tm (x) = Tm,i +

q′ ′. p X ṁ . c p

standard patterns of inverse cubic spinel magnetite (Fe3O4) crystal structure, showing six diffraction peaks at 2θ about 35.3°, 41.6°, 50.7°, 63.1°, 67.7° and 74.5° marked by their indices (220), (311), (400), (422), (511), and (440), respectively [33]. Comparing these XRD pattern reveals that peak of Graphene in 2θ = 10.9 is completely removed in curve Fe3O4/Graphene because of Fe3O4 covering Graphene sheets that prevents the re-accumulation of Graphene sheets together. Also it should be noted that the stoichiometric relations reveal the presence of 79%.Wt of Fe3O4 nanoparticles in comparison to 21%.Wt of Graphene; such ratio describes the disappearance of wide peak of GO in the XRD pattern. Indeed this high content of Fe3O4 nanoparticles suppress the restacking of Graphene sheets. This finding is consistent by the results of Thu research work [27]. The crystal size of Fe3O4 particles over Graphene sheets is obtained as 4.94 nm by using the Scherer's equation [34] as follow:

(5)

Where Tm,i, p, ṁ, Cp and X are the fluid temperature at the inlet of the test section, the surface perimeter, the mass flow rate, the heat capacity and axial distance, respectively. To start the experiment process in the first step the circulator bath was turned on. After reaching the temperature to the desired value the pump and power supply was set to the operating range. After about 30 min the system reach to the steady state and then the temperatures were measured. 3. Results and discussion

d= 3.1. Characterization results

K. λ β. cos(θ)

(6)

K is a dimensionless shape factor with typical value of about 0.9, λ is the X-ray wavelength of tube (Cobalt, 0.173 nm), β is the line broadening at half the maximum intensity and θ is the Bragg angle. Fig. 3(b) shows FTIR spectra of the obtained Graphene oxide and

The main aim of X-ray Diffraction is to specify the crystal structure of the materials. Fig. 3(a). Shows the XRD pattern of Graphene oxide and hybrid Fe3O4/Graphene. The results in curve are in agreement with

Fig. 3. a) XRD patterns, b) FTIR spectra graph and c) TEM images of Graphene oxide and Fe3O4/ Graphene nanohybrid.

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Fe3O4/Graphene nanohybrid. The presence of different oxygen functionalities in the curve Graphene oxide was confirmed at 3434 cm− 1 (OeH stretching vibrations), 1732 cm− 1 (C]O stretching of carbonyl and carboxyl groups located at edges of the GO networks) and 1056 cm− 1 (CeO stretching vibration of epoxide) [35]. The peak 1732 cm− 1 in the spectrum of Graphene oxide (double bond of carbon and oxygen) is shifted to 1616 cm-1 in curve Fe3O4/Graphene which leads to the formation of COOe after decoration of Graphene oxide with Fe3O4. The peak in 617 cm− 1, is related to FeeO stretching vibration in curve Fe3O4/Graphene. In comparison with pure Fe3O4, in which this peak appears in 568 cm− 1 [36], it can be concluded that in the presence of Graphene oxide, this peak is transferred to the higher wave number. This result represents the linkage of Fe3O4 with eCOOe groups on the Graphene oxide. Fig. 3(C-1) represents the TEM image of Graphene sheet in which the layers of Graphene can be seen clearly, and also Fig. 3(C-2) shows the TEM images of Fe3O4/Graphene nanohybrid. These figures reveal that Graphene sheets are covered completely by Fe3O4 nanoparticles. The Fe3O4 nanoparticles are in spherical shape. Presence of Graphene sheets prevents agglomeration and leads to the lower particle size. The results indicated that the average size of particles is about 5 nm which is consistent by the results of Scherer's equation.

Table 1 Nanofluids zeta potential. Nanofluid

Zeta potential(mv)

Graphene oxide Hybrid Fe3O4/Graphene Fe3O4

− 43.5 − 40.2 − 38.7

stability of the prepared nanofluids. 3.3. Uncertainty Uncertainty analysis is one of the important factors in experimental investigations that should be calculated for every studied parameter. Uncertainties mainly related to the instrumentation inaccuracies, data acquisition errors, and data analysis faults [38]. Moffat theory has been used for estimation of uncertainty in this research [39]. According to the Moffat theory D is a function of different variables (Xi) and it can be shown as D = f(× 1, ×2, …,Xn). Each variable contribution is approximated by Eq. (7).

UD = D

2

2

2

⎛ ∂X1 ⎞ + ⎛ ∂X2 ⎞ +…+⎛ ∂Xn ⎞ ⎝ X1 ⎠ ⎝ X2 ⎠ ⎝ Xn ⎠ ⎜

⎟

⎜

⎟

⎜

⎟

(7)

Uncertainty results in the determination of thermal conductivity, density, viscosity and convective heat transfer coefficient, calculated as a mean standard error, are shown in Table 2.

3.2. Nanofluid stability Effect of pH and time on the stabilization of nanofluids has been investigated in Fig. 4. As it can be seen among five different pH values of 3, 5, 7, 8 and 10, nanofluids with pH of 8 and 10 are stable even after two weeks. However, since in industrial applications, use of neutral pH is more suitable, so in this study a nanofluid with pH of 8 was used. The stability of the dispersed particles is affected by their surface charge or zeta potential. The significance of zeta potential (negative or positive) is that its value can be related to the stability of colloidal dispersions. It is well known that suspensions with zeta potential above 30 mV are physically stable and above 60 mV show excellent stability while a suspension below 20 mV has limited stability, and below 5 mV undergoes pronounced aggregation [37]. Table 1 represents the results of zeta potential for three nanofluids. As it can be seen zeta potential of Graphene oxide is −43.5 mV, while it is − 38.7 mV for Fe3O4 nanofluid. On the other hand zeta potential for nanofluid containing Fe3O4/ Graphene nanohybrid (pH of 8) is − 40.2 mV, which is between Graphene oxide and Fe3O4 nanofluids. These values confirm the good

3.4. Nanofluids density Fig. 5(a) represents the density change by mass fraction for three different nanofluids of Fe3O4, Graphene oxide and Fe3O4/Graphene nanohybrid at room temperature. The density of nanofluid increases by concentration addition; however, the increase in density is negligible. For example, density increases from 998.8 kg/m3 for water to 1000.2, 1002.6 and 1006.2 kg/m3 for Fe3O4/Graphene nanofluids with concentrations of 0.1, 0.5 and 1%.Wt. The main reason for the density enhancement by addition of nanoparticles to the fluid is attributed to the fact that the mass added by nanoparticles to the fluid system is significantly larger than the increased volume made by addition of nanoparticles. Note that as the results in Fig. 5(a) represents, since the density of Fe3O4 is about %79 by weight of hybrid, the density of hybrid nanofluid is closer to the Fe3O4. Based on the experimental results and Fig. 4. Effect of pH and time on the stabilization of Fe3O4/Graphene nanofluid.

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Viscosity of Fe3O4/Graphene nanofluids were correlated by different theoretical models [40,42]. Among them, two models which are shown by Eqs. (10) and (11) correlated more successfully:

Table 2 Maximum uncertainty in experimental parameters and measurement devices. Parameters

Type

Uncertainty (%)

Temperature (T) Density (ρ) Velocity (u) Viscosity (μ) Thermal conductivity (K) Convective heat transfer (h)

K type Thermocouple Pycnometer Acrylic Rotameter flow meter Brookfield digital viscometer KD2-Pro Experimental setup

± 2.2 ± 0.2 ±2 ±1 ±5 ± 5.9⁎⁎

⁎,⁎⁎

μ = (1 − 0.1 × ∅ + 15 × ∅2) × μ f μ=

reported models in the literature for density of nanofluids, two theoretical models were used for correlation:

ρ=

ρf (1 − 2.6 × ∅)0.01

(11)

where ∅ and μf are particle volume fraction and base fluid viscosity, respectively. In which the viscosity of nanofluid is depended on base fluid viscosity and weight fraction of particles, respectively. Fig. 6(b) represents the consistency of experimental viscosity data measurements with two theoretical correlations.

The (h) uncertainty is calculated by moffat theory.

ρ = 1003.4 + 30 × ∅ − 0.18 × T; 5 < T ( °C) < 40

μf (1 − 1.6∅)0.75

(10)

(8) 3.6. Thermal conductivity (9) The thermal conductivity of Fe3O4/Graphene nanofluid measured at different temperatures for various concentrations. As illustrated in Fig. 7, the thermal conductivity of the nanofluids has an increasing trend with mass fraction as well as temperature. For instance, thermal conductivity of water is measured to be 0.59 W/m.K, while Fe3O4/ Graphene nanofluid with weight percentage of 0.1 and 0.5 augmented to be 0.64 and 0.69 W/m.K at 40°C, respectively. For nanofluid with 1%.Wt Fe3O4/Graphene nanoparticles, thermal conductivity reaches to 0.78, indicating an improvement of 32% at 40°C. Note that the increase in thermal conductivity is nonlinear both for mass fraction and temperature. The linearity and nonlinearity of thermal conductivity enhancement with mass fraction depends on base fluid and the nature of the nanoparticle [43]. Such enhancement can be due to the high thermal conductivity of Graphene and Fe3O4 nanoparticles. In addition the particle-particle distance (mean free path) decreases when mass fraction increases, leading to the frequency rising of lattice vibration, which is known as the percolation effect of heat transfer [44]. Furthermore, in higher temperatures the inter particle and inter molecular adhesion forces are weaker. This fact causes to an increase in Brownian motion and random movement of particles, leading to an enhancement in thermal conductivity of nanofluids at higher temperatures. Fig. 7 illustrated the comparison of Fe3O4 thermal conductivity and hybrid Fe3O4/Graphene nanofluids. Since the thermal conductivity of Graphene is more than Fe3O4, thermal conductivity of hybrid Fe3O4/Graphene nanofluids is more than Fe3O4 nanofluids at all concentrations. Also the formation of cluster in Fe3O4/Graphene nanofluid with respect to the Fe3O4 nanofluid is a basis for higher thermal conductivity. Particle size distribution of nanofluids was measured, so the average size of Fe3O4 and Fe3O4/Graphene nanoparticles is around 60.4 nm and 327 nm, respectively. Creation of larger particle size of hybrid Fe3O4/ Graphene may be attributed to the existence of Graphene sheets. More over formation of clusters may lead to the bigger particle; because Graphene sheets has a higher tendency to stick to each other and forming clusters compared to the spherical Fe3O4 nanoparticles.

where ∅, T and ρf are volume fraction, temperature and base fluid density, respectively. Fig. 5(b) represents these correlation results. Comparison of these data with theoretical models indicates that there is a good consistency between the experimental data and theoretical models. 3.5. Nanofluids viscosity The increase in concentration of particles leads to enhancement in heat transfer, but on the other hand viscosity of the fluid increases either [40,41]. Fig. 6(a) represents the viscosity change by weight fraction of Fe3O4/Graphene nanohybrid in different temperatures. As it can be seen, increasing the mass fraction of nanoparticles augmented the viscosity of nanofluid. For instance, at 20 °C, the viscosity of Fe3O4/ Graphene nanofluid increases from 0.99 mPa.s (pure water) to 1.03, 1.06 and 1.15 mPa.s at concentrations of 0.1, 0.3 and 0.5%.Wt, respectively. Such viscosity enhancement, especially in lower concentrations of Fe3O4/Graphene nanohybrid is negligible enough for industrial applications; moreover by rising the temperature, the viscosity decreases. For example, the viscosity of nanofluid with concentration of 0.1%.Wt decreases from 1.03 mPa.s (measured at 20 °C) to 0.82 and 0.68 mPa.s at 30 and 40 °C, respectively. In general, nanoparticles tend to accumulate by attractive forces (van der Waals), but the repulsive forces (electrostatic) provided by surfactant, prevents the attachment of nanoparticles. By addition of nanoparticles concentration, the attractive force become stronger than repulsive force and as a result of this fact particles tend to stick together, leading to an increase in viscosity of nanofluids. Another reason for viscosity improvement attributed to the internal shear stress addition of fluid layers in the presence of nanoparticles. The nanofluids viscosity diminishment by rising of temperature is due to the weakening of the inter particle and inter molecular adhesion forces.

Fig. 5. a) Density change by mass fraction for three different nanofluids and b) comparison of developed correlations for density of Fe3O4/Graphene nanofluid with experimental data.at room temperature.

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Fig. 6. a) Viscosity change by mass fraction in different temperatures and b) comparison of developed correlations for viscosity of Fe3O4/Graphene nanofluid with experimental data at room temperature.

calculated by Colebrook equation [46], given in Eq. (13)

f=

3.7. Heat transfer coefficient In order to demonstrate the validity of the experimental setup, comparisons of experimental data with the previously published expressions was performed for the case of water flowing through a tube with constant heat flux. A traditional expression for calculation of heat transfer in turbulent flow in smooth tubes is recommended by Gnielinski [45] shown in Eq. (12): f 8

(Re−1000) Pr

1 + 12.7

f 0.5 (Pr 2 3 8

()

(13)

Fig. 8(a) displays the comparison of calculated Nusselt number by Gnielinski formula and present work evaluations for water. As it is clear the present experimental study obtaining is in good agreement with the estimation of previous correlations of Gnielinski. Also to confirming the data integrity, the water experimental obtaining are compared by the Blasius equation [47]. Fig. 8(b) illustrates the validation of the friction loss data from the above-mentioned equation and the experimental investigation has an error rate of < 5.95%. After validation of experimental setup, in the next step, the convective heat transfer coefficient was evaluated for Fe3O4 and Fe3O4/ Graphene nanofluids. Fig. 9(a) shows the heat transfer study of DI water based nanofluids (with concentration of 0.1%.Wt nanoparticles) at different Reynolds numbers. The results indicate that convective heat transfer coefficient increases significantly for nanofluids compared to the base fluid. For instance, the convective heat transfer coefficient in the Reynolds number of 2180 for water is 723 W/m2 K, while it increases to 842 and 916 W/m2 K for Fe3O4 and Fe3O4/Graphene nanofluids, respectively. For Reynolds number of 4248, heat transfer coefficient increases from 1728 W/m2 K for water to 1874 and 1977 W/ m2.K for Fe3O4 and Fe3O4/Graphene nanofluids, respectively. The reason for such enhancement can be attributed to the fact that by dispersing nanoparticles in water, the surface area for heat transfer increases and the temperature gradient between different layers of fluid decreases (due to increased thermal conductivity). By comparing heat transfer coefficient of Fe3O4 and Fe3O4 /Graphene nanofluids, it can be concluded that the heat transfer coefficient of Fe3O4/Graphene nanofluid is more than Fe3O4 nanofluid. This effect can be explained by the presence of Graphene sheets with high thermal conductivity in the Fe3O4/Graphene nanofluid. Increase in Reynolds number causes to improvement of Brownian motion and extra free movement of particles. Fig. 9(b) depicted the variation of average wall temperature versus Reynolds number for Fe3O4 and Fe3O4/Graphene nanofluid. The wall

Fig. 7. Variation of thermal conductivity of Fe3O4 and Fe3O4/Graphene nanofluids with various mass fractions.

Nu =

1 (1.82 log10 Re−1.64)2

1.5 < Pr < 2000&3000 < Re < 5 × 106 − 1) (12)

The fraction factor for fully developed turbulent flow can be

Fig. 8. a) Comparison of Nusselt number from Gnielinski formula and present work for water and b) validation of experimental setup frictional head loss function of Reynolds Number for water.

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Fig. 9. a) Comparison of heat transfer coefficient nanofluids (0.1%.Wt) with base fluid and b) tube wall's temperature at various Reynolds number.

water temperature of 45 °C. As it is shown the slope of the line is reduced when nanofluid is added to the pure water. For example, water demands decrease from 80.73 ml/min for water to 61.25 ml/min and 72.5 ml/min for Hybrid Fe3O4/Graphene and MWNTs respectively. Fig. 11(b) detailed the liquid to air flow rates variation versus cooling tower efficiency. Addition of the liquid to air flow rate ratio leads to subsiding of tower efficiency. It could be inferred that by ascending flow rate ratio the fluid hold up will go up; thus, fluid with higher thickness will form on packing surface. This happening result in temperature gradient between layers of fluid, so effective surface area diminished. All the applied nanofluids has shown a higher efficiency respect to the water and this observation is related to the improved fluid thermal conductivity and extra available surface area for heat transfer; this is a basis for enhanced heat transfer between fluid/air and then outlet fluid temperature reduced more than pure water. The evaporation of water molecules reduced addition of nanoparticles, so the water demands receded accordingly. Additionally the typical form of heat transfer in present wetted cooling column is changed. So the synthesized nanofluids have promising properties for application as a heat transfer fluid in wet cooling tower regarding of water usage and thermal efficiency.

temperature has a prevailing tendency to decrease by rising of Reynolds number and this occurrence is due to the improvement of heat transfer coefficient by entering of fluid in turbulence regime. All in all by comparing the wall temperature in a wide range of Reynolds number, nanofluids have a lower wall temperature compared to the pure water. The enhanced heat transfer properties of nanofluid confirms that the nanofluid will reduces the heat accumulation in tube wall and as result heat transfer will augmented accordingly. So as it is shown in Fig. 9(b) the wall temperature for Fe3O4/Graphene is lower than Fe3O4 nanofluids. As mentioned before the Fe3O4/Graphene nanofluid has a higher thermal conductivity and convection heat transfer coefficient compared to the Fe3O4 nanofluid; this superiority is a basis for better heat transfer of Fe3O4/Graphene nanoparticles at the tube wall and creation of a radially uniform temperature contour across the tube. 3.8. Wettability effects of Fe3O4/Graphene nanofluid Wettability is defined as the capability of the fluid to hold its contact with a solid surface. In most of thermal equipment the solid surface is advised for better exchange of heat between multiple mediums such as shell and tube heat exchangers, air coolers and etc. The surface forces (cohesive and adhesive) are controlled the wettability of the fluids on different surfaces. So, the wettability is one of the important factors, especially for evaluation of the friction factor and heat transfer coefficient of multiple-phase flow in industrial applications [46]. The Adhesive forces cause to spread droplet of liquid over the solid surface. In opposite, the liquid droplets refrain from being in contact with the surface due to the cohesive impacts. Usually for estimation of the wettability the contact angles (θ) is evaluated, which demonstrate the wetting intensity of the fluid (so that θ > 90° means less wetting and θ < 90° refer to more wetting of the fluid). Fig. 10 depicted the contact angles image for hybrid Fe3O4/Graphene nanofluid at 25 °C and various concentrations which advances all over of a copper bed surface (because of the manufactured material of the convection heat transfer setup). As it is illustrated in Fig. 10, by addition of particles loading the contact angle is reduced. The contact angle of the base fluid on the copper surface was 99.3°, which it was decreases to 93.6°, 92.1°, 90.4° at 0.1%.Wt, 0.3%.Wt and 0.5%.Wt for hybrid Fe3O4/Graphene nanofluid, respectively. Base fluid included of nanoparticles has prominent property which is origin of the cohesive force diminishment and consequently enhancement of wettability. As much as the contact angle is higher the heat transfer coefficient will be lower [48].

4. Conclusion In conclusion, in the present work, a hybrid of Fe3O4/Graphene nanohybrid was synthesized to be applied in a water-based nanofluid. The Fe3O4 nanoparticles with a small diameter of 5 nm were dispersed uniformly over the Graphene sheets. The effect of pH was evaluated in the stability of the nanofluid and it was found that nanofluid with a pH of 8 is stable by a zeta potential of − 40.2 mV. Rheological properties of nanofluids including density and viscosity were evaluated and theoretical correlations in good agreement with experimental data were developed. It was found that the increase in density and viscosity, especially in low concentrations of nanoparticles was negligible enough for industrial applications. Moreover thermal characteristics of nanofluid including thermal conductivity and convective heat transfer coefficient

3.9. Cooling tower In our previous work [38], we have studied the Multi-walled carbon nanotubes (MWNTs) nanofluid affectability in wet cooling tower regarding of water and energy expenditure. The present study describes the heat transfer effects of hybrid Fe3O4/Graphene in cooling tower and then the comparison with previous work is made [38]. Fig. 11(a) indicates the evaporation variations by passing time at cooling tower inlet

Fig. 10. Contact angle image of the base fluid and the hybrid Fe3O/Graphene nanofluid at different concentrations.

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Fig. 11. a) The water usage of cooling tower vs. time at inlet water temperature of 45 °C and b) Tower efficiency change at various flow rate ratio of liquid/air in liquid inlet temperature of 40 °C [38].

were investigated experimentally. The results indicated that thermal conductivity improved by 14–32% for a mass fraction of 1%.Wt for Fe3O4/Graphene nanofluids at 20–40 °C. Furthermore, compared to the base fluid, for Fe3O4 and Fe3O4/Graphene nanofluids at Reynolds number of 4248, an enhancement of 8.5% and 14.5% in heat transfer coefficient was observed respectively. All these results offer that the stable and cost effective Fe3O4/Graphene nanofluid can have very promising applications in heat transfer systems.

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