Thermophysical and Forced Convection Studies on (Alumina + Menthol)-Based Deep Eutectic Solvents for Their Use as a Heat Transfer Fluid.

The current work reports the thermophysical and flow measurements of novel thermal solvents based on deep eutectic solvents (DESs) and alumina-based nanoparticle-dispersed deep eutectic solvents (NDDESs) for its use as a potential solar energy storage medium. The DESs were synthesized using a hydrogen bond donor (i.e., oleic acid) and a hydrogen bond acceptor (i.e., dl-menthol) by using the COSMO-SAC-predicted equimolar ratio at a temperature of 350.15 K. Thereafter, NDDESs or nanofluids were formed by dispersing different volume fractions (0.001, 0.005, 0.0075, and 0.01) of Al2O3 nanoparticles in the DESs. The optimum volume fraction (0.005) of Al2O3 nanoparticles was selected through their thermophysical properties (density, viscosity, thermal conductivity, and specific heat capacity) and its agglomeration or stability behavior. As expected, NDDESs with a 0.005 volume fraction gave a higher enhancement in thermal conductivity, viscosity, heat capacity, and density as compared to DESs. To evaluate the heat transfer coefficient, forced convection experiments were conducted in a circular test section for both DESs and NDDESs under laminar conditions (Re = 124, 186, and 250). The enhancement of the local heat transfer coefficient was found to be higher when compared to their thermophysical properties. This was due to the nanoparticle migration resulting in a non-uniform distribution of both thermal conductivity and viscosity fields, which was inherently found to reduce the thermal boundary layer thickness. In the final section, the heat transfer coefficient and the Nusselt number were also validated with COMSOL Multiphysics simulations.

Introduction

Concentrating solar power (CSP) is currently recognized as a valuable source of renewable energy.[1] The stored thermal energy can be utilized in various thermodynamic cycles such as Brayton cycle to generate turbine power from gas turbine engines. The advantage of CSP is that the energy stored in daylight can be used at nighttime where the thermal fluid can potentially reuse the solar energy. The main drawback includes its elevated cost as compared to conventional energy sources. For this reason, the scientific community aims to improve the overall efficiency of these solar plants. One of them is to improve the efficiency of the heat transfer processes that occur in this application. CSP plants usually adopt a technology involving parabolic cylindrical collectors, which in turn uses a heat transfer fluid for the storage and transport of heat. Keeping the CSP process in mind, increasing the heat transfer effect is a key deliverable usually obtained by enhancing the thermophysical properties of these fluids. The current study is thus meant for generating turbine power using the CSP energy storage.

In CSP, the solar energy is usually concentrated using mirrors and lenses and stored in a thermal fluid. The working fluid used in the CSP plant plays an important role in determining the overall efficiency of the system. The conventional thermal fluids have low-to-moderate thermal stability and heat storage capacity, which results in high operating costs.[1] Researchers have tried ionic liquids (ILs) as one of the alternatives for heat transfer fluid for future generations.[2] However, ILs are highly viscous, costly, and difficult to synthesize. Application of ILs in solar collector applications[3,4] have been recently reported. Wu et al.[3] have focused the applicability of 1-butyl-3-methylimidazolium hexafluorophosphate, 1-octyl-3-methylimidazolium hexafluorophosphate, 1-butyl-3-methylimidazolium bis-trifluromethane sulfonamide, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-octyl-3-methylimidazolium tetrafluoroborate, and 1-butyl-3-methylimidazolium bis-trifluromethane sulfonamide as a thermal energy storage medium for solar collectors. The storage density of 1-octyl-3-methylimidazolium hexafluorophosphate was found to be 378 MJ/m3. Moens and Blake[4] have performed an overall assessment of ILs for its use as a heat transfer fluid in solar parabolic trough systems.

To lessen the cost associated with ionic liquids, many countries have shifted to molten salts (KNO3, NaNO2, and NaNO3) as a heat transfer fluid in CSP. However, it also suffers from the problem of high freezing point when the temperature drop reaches below 473.15 K and thus possesses a maintenance problem.[5] Other issues with molten salts are their low specific heat capacity values and their corrosive nature. As compared to other green solvents such as ILs or molten salt mixtures, deep eutectic solvents (DESs) are inexpensive and are nowadays a substitute for thermal fluids. The extended benefits of using DESs would be surpassing the inherent shortcomings of comparable green solvents, particularly with respect to density and viscosity,[6,7] which are essential parameters for heat transfer. In this regard, DESs have several excellent physical and chemical properties including high thermal stability, low melting point, higher air and moisture stability, nonflammability, high heat capacity, and low density.[8−11]

DESs are the product of two or more entities in which hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs) are combined to form liquids upon mixing with melting points below those of the individual components.[12−14] Some researchers also designate DESs as low melting mixtures (LMMs), deep eutectic ionic liquids (DEILs), or low transition temperature mixtures (LTTMs).[15] Overall, DESs have a low volatility, have a wide liquid range, and are water-compatible, nontoxic, and biocompatible, and some of them are biodegradable.[16,17] Other advantages of DESs include low cost of its constituents, ease of preparation, tunable physicochemical properties, and negligible vapor pressure. Some typical hydrogen bond donors and acceptors are listed in Table .

Table 1

Typical Salts and Hydrogen Bond Donors of Deep Eutectic Solvents

In addition to that within the past decade, nanofluids have gained attention for the thermal property enhancement of base fluids. Earlier results have pointed out the fact that thermal conductivity of the IL-based heat transfer fluid increases as the diameter of the nanoparticle is reduced. On the other hand, the major drawback of nanofluids is that the coefficient of friction and pressure drop also increases with volume fraction. Thus, an optimum volume or mass fraction of nanoparticles with base fluid needs to be chosen based on both thermophysical properties and the flow regime. Further, the results also suggest that the nanofluids do improve the convective heat transfer, particularly at the entrance region. Based on an earlier work by Li et al.,[18] the local heat transfer coefficient increases by 60% for a Cu–water-based nanofluid containing 2% Cu nanoparticles by volume, while on the other hand, the nanofluids possess only an effective thermal conductivity 12.5% higher than that of the base liquid. This may be due to the particle migration that results in a non-uniform distribution of thermal conductivity and viscosity fields, which ultimately reduces the thermal boundary layer thickness. Overall, the results clearly show that the use of nanofluids significantly improves the convective heat transfer, particularly at the entrance region. However, the increase in Reynolds number or volume fraction of particles also results in an increase in heat transfer and pressure drop. For example, in the case of water–TiO2 nanoparticles, the heat transfer rate of nanofluids with a concentration of 0.002 was higher than that of the base fluid, while both of them had the same pressure drop in the low Reynolds numbers. Therefore, dilute nanofluids may be recommended and adopted in this work with DES-based heat transfer fluids at low Reynolds numbers. Hence, in our studies, nanoparticle-dispersed DESs (NDDESs) have been explored using spherical Al2O3 nanoparticles of 70 nm. Additionally, the nanoparticles have proven to have a negligible effect on the physical properties (density and viscosity) of the base fluid, thereby limiting the pressure drop and also the coefficient of friction.

The idea of DESs as a base fluid is a novel concept, since DESs behave similarly to ILs in terms of physical and thermal characteristics. The idea of menthol-based DESs was first proposed by Florindo et al.[19] They have investigated dl-menthol with a series of HBDs like pyruvic acid, acetic acid, l-lactic acid, and lauric acid. On a similar note, dl-menthol with oleic acid was taken as the two components of DESs in this work. Nanoparticle-dispersed DESs (NDDESs) have been explored to increase the specific heat capacity of the pure DESs without any change in their thermal stability. An increased specific heat capacity indicates an efficient heat transfer fluid in terms of energy storage. Many researchers used Al2O3 nanoparticles as an addition to a base fluid so as to enhance its thermal properties (thermal conductivity and specific heat capacity). They have also been proven to have a negligible effect on the physical properties (density and viscosity) of the base fluid.[2] Keeping these advantages in mind, the current work has adopted spherical Al2O3 nanoparticles to prepare the desired NDDESs.

Results and Discussion

Density and Viscosity

As expected, the density of both DESs and NDDESs was found to decrease with increasing temperature (Figure ). This is due to the fact that the thermal expansion generally results in a lower density with an increase in temperature. The measured densities were also compared with the commercially available thermal fluids[20] as well as the ILs.[21] It was found that the experimentally measured density of DESs and NDDESs of different volume fractions (0.001, 0.005, 0.0075, and 0.01) was also lower than that of water.

Figure 1

Density variation of DESs and NDDESs.

The shear stress and shear strain for both DESs and NDDESs were depicted in Figures S1–S5 of the Supporting Information, where it was observed that the fluid obeyed a Newtonian behavior.[22] Further, the viscosity of DESs and NDDESs was also measured as a function of shear rate, where the Newtonian behavior[22] was again confirmed (Figure S6–S10). The viscosity of DESs and NDDESs is plotted as a function of temperature in Figure . The decrease in viscosity of DESs was around 92% as the temperature increased from 298.15 to 423.15 K. The viscosity of DESs was found to be very close to that of water at a higher temperature. On a similar note, the decrease in viscosity of NDDESs was found to be ∼95% as the temperature increased from 298.15 to 423.15 K. Overall, the addition of nanoparticles had a less pronounced effect at a higher temperature, thereby enabling their use at a higher temperature in CSP. The experimentally measured viscosity was also compared with existing models, which were previously used[23−25] for nanofluids. Initially, the Einstein model[23] was used for calculating the viscosity of fluid containing a low volume fraction (<0.002) of spherical particles. The model is given below:Brinkman[24] modified the Einstein fluid model for concentrated nanoparticles asThereafter, Batchelor[25] modified the Einstein model while considering the Brownian motion of the particles. The expression for the Batchelor model is mentioned belowwhere μNDDES and μDES are the viscosity of NDDESs and DESs, respectively, and ϕ is the nanoparticle volume fraction. Figure S11 of the Supporting Information shows that all the models underpredict the actual experimental values by an order of 10%. This is because all the models (eqs –3) have considered nanoparticle volume fraction. These models obviously did not incorporate the effects such as agglomeration of nanoparticles and the liquid layering on nanoparticles.

Figure 2

Viscosity of DESs and NDDESs as a function of temperature.

Thermal Conductivity

The thermal conductivity of all NDDESs, when compared to the respective DESs, indicates an increase in thermal conductivity as shown in Figure . It should be noted that during the measurement of thermal conductivity, the convection current should be avoided as the thermal analyzer considers only the conduction mode of heat transfer. This is true since heating the sample at a higher temperature creates natural convection currents, which creates a density difference in the medium. In this regard, the experiment was performed using a small diameter tube so that the natural convection current is minimized. The thermal conductivity of DESs has shown to decrease slightly with increasing temperature. As compared to DESs, the thermal conductivity of NDDESs gave an approximate average increase of ∼10%. The increase in the thermal conductivity is similar to those observed for TiO2–water[26] and Al2O3.[27,28]

Figure 3

Temperature variation of thermal conductivity of DESs and NDDESs.

The Maxwell model[29] for spherical nanoparticles with a homogeneous suspension was considered while modeling the thermal conductivity values. This is given below as:An improvement (namely, the Bruggeman model[30]) predicted a higher agreement than the Maxwell model because it considers the clustering of nanoparticles. The Bruggeman model[30] for calculating the thermal conductivity of NDDESs is given in eq . Both models are compared in Figure S12 of the Supporting Information.

The specific heat capacity of DESs was found to increase with temperature (Figure ). The specific heat capacity of NDDESs was found to be higher than that of DESs. As compared to base fluids (namely, DESs), the specific heat capacity of NDDESs increased by 6%, 15%, 27%, and 50% corresponding to nanoparticle volume fractions of 0.001, 0.005, 0.0075, and 0.01, respectively. Overall, the specific heat capacity increases with the concentration of nanoparticles, as shown in Figure . Similar phenomena were also observed with Cu nanoparticles.[31] This can be attributed to the formation of an internal structure within the nanofluids, generating a specific contact between DESs and alumina nanoparticles. One possible outcome of this is a formation of a chain-like nanostructure that is similar to an infiltrating network as observed in aggregated suspensions such as nanofluids. Here, it is the DESs that initiate this nanostructure[32] based on the π–π stacking of its menthol moiety. This nanostructure formation is much larger than that of conventional nanofluids without DESs. It is this nanostructure that eventually contributes to the enhanced specific heat capacity and also explains a higher particle size (i.e., 200 Å) as observed in dynamic light scattering. It implies that the DESs are primarily responsible for the enhanced specific heat capacity of DES-based nanofluids. This interaction or contact depends on the nature of both DESs and NDDESs and deserves merit in evaluating the same interaction or contact using molecular dynamics.

Figure 4

Temperature variation of specific heat capacity of DESs and NDDESs.

In terms of the thermal properties (Figures and 4) reported above, NDDESs can be recognized as more efficient than DESs. Looking at their physiochemical properties, NDDESs at a volume fraction of 0.005 were chosen as an optimum choice based on their stability (zeta potential, 97.4mV), density (Figure ) and viscosity (Figure ), thermal conductivity (Figure ), and specific heat capacity (Figure ). The 0.001 volume fraction is not selected as it gave a specific heat capacity and thermal conductivity values similar to NDDESs with a 0.005 volume fraction. Nanoparticle concentrations at a higher volume fraction (>0.005) led to practical difficulty in pumping consideration and agglomeration behavior. Hence, this negated our choice. This led us to choose a 0.005 volume fraction NDDESs as the optimum value with respect to the thermophysical properties and stability. Further, the stability behavior of the nanofluids was checked by zeta potential and visual observation under stagnant conditions and was also subjected to centrifugal force at various speeds for 5 min. Here, the speeds were varied from 5000 to 15,000 rpm. The nanofluids were considered stable only when no particles or sediments were observed even after 10 min.

Forced Convection Studies

The COMSOL simulations have been performed in COMSOL Multiphysics (version 5.2a). Initially, the space dimension as 2D axisymmetric was selected. A no-slip boundary conditions and a uniform heat flux were applied to the wall. A time-dependent study was performed so as to ascertain steady state. The dimensions of the test section were assumed to be rectangular (length, 1000 mm; width, 9 mm). The two-dimensional tube geometry was generated by a COMSOL built-in meshing tool, where a total of 228,680 mesh elements were created. Experimentally measured thermophysical properties (density, viscosity, conductivity, and specific heat capacity) as given in Figures –4 are used for the simulations. Thereafter, the simulation was started with an initial guess, which shall help us in solving the velocity and temperature profile. A uniform heat flux of 13,312 W/m2 was applied to the wall. This was the same flux as used in Figure via heating tape. To solve the energy equation, velocity information is necessary. This is obtained by solving the continuity and momentum equation (eqs –14). Here, the flow coupling was added explicitly as provided under the Multiphysics section within COMSOL. While Figures –7 discuss the heat transfer performance of DESs, Figures –10 depict the NDDES performance.

Figure 15

Schematic of forced convection experimental setup.

Figure 5

Temperature profile along the test section for DESs.

Figure 7

Nusselt number of DESs as a function of x/D.

Figure 8

Temperature profile along the test section for NDDESs at a 0.005 volume fraction.

Figure 10

Nusselt number of NDDESs (0.005 volume fraction) as a function of x/D.

Figure signifies the temperature profile of DESs along the axial distance of the test section with three different Reynolds numbers within the laminar regime. Figure represents the heat transfer coefficient of DESs along the axial distance at a heat flux of 13,312 W/m2 in three different Reynolds numbers. The experimental heat transfer coefficient was compared with the numerical results, where it gave a negligible deviation. The DESs gave enhanced heat transfer coefficient along the entire axial distance, and the heat transfer coefficient decreases with axial distance. As expected, the heat transfer coefficient was also found to increase with an increase in Reynolds number. Figure represents the Nusselt number of DESs along the axial distance at three different Reynolds numbers, where the Nusselt number increases with an increase in Reynolds number. Al2O3 (spherical) nanoparticles with a volume fraction of 0.005% have been chosen for both experiment and simulation. A similar phenomenon is observed for NDDESs with respect to temperature profile (Figure ), heat transfer coefficient (Figure ), and Nusselt number (Figure ).

Figure 6

Heat transfer coefficient of DESs as a function of x/D.

Figure 9

Heat transfer coefficient of NDDESs (0.005 volume fraction) as a function of x/D.

In both cases (DES and NDDES), it has been found that the inside surface temperature of the tube is higher with a decrease in Reynolds number. However, a decrease in Reynolds number led to an ∼10% enhancement in the surface temperature, which is evident near the entrance region. The hydrodynamic entry length and thermal entrance length are given by xh = 0.05ReD and xt = 0.05RePrD,[33−37] respectively. It should be noted that a 1 m length pipe was sufficient for a flow to be considered hydrodynamically developed, but the same cannot be said of its thermal layer. In both DES and NDDES, at the entrance of the pipe, the heat transfer coefficient is very large due to which the boundary layer thickness is very small. It is found that the boundary layer thickness starts increasing while the heat transfer coefficient decreases along the pipe length. An appreciable increase in the coefficient of heat transfer was attributed to the increased thermophysical properties of DES nanofluids and a delay in the development of the boundary layer in the entrance areas. This behavior indicates that measures could be taken such as creating “artificial entrance” regions along a pipeline to maximize the performance of these novel nanofluids. The flow is not thermally developed as the value of Prandtl number is large for both DES and NDDES fluids.

Overall, the thermal entrance length of the nanofluid flows had a longer length scale when compared to only DES flow. The enhancement of the local heat transfer coefficient was higher in magnitude when compared to the increase in the effective thermal conductivity within the test section. Thus, the use of NDDES nanofluids significantly improves the convective heat transfer, particularly at the entrance region. This may be due to the particle migration resulting in a non-uniform distribution of both thermal conductivity and viscosity, which eventually reduces the thermal boundary layer thickness. The benefit of NDDESs as a heat transfer fluid shall be determined based on the consideration between the increase in heat transfer performance and the increase in pumping power. Further, the stability of nanoparticles is another concern. Their agglomeration ability is a critical problem faced in the practical application of nanofluids. This affects the properties of nanofluids and impacts the heat transfer performance of nanofluids. The agglomerates can have various sizes and configurations depending primarily on the elapsed time. They can invariably affect the thermal conductivity of nanofluids. This agglomeration may also be due to the nanofluid preparation and the experimental study time along with different time durations of the experimental study. However, the use of surfactants can increase their stability. In some of the earlier reported work,[31,32] these may be reached under low pH conditions, thereby making nanofluids difficult in many application systems.

Conclusions

Heat transfer fluid based on deep eutectic solvents was synthesized using a hydrogen bond donor (i.e., oleic acid) and a hydrogen bond acceptor (i.e., dl-menthol). An equimolar ratio of hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA) was predicted by COSMO-SAC predictions, and the same equimolar ratio was used in the synthesis of DESs. Thereafter, NDDESs were prepared with four different Al2O3 at different concentrations (0.001, 0.005 0.0075, and 0.01 volume fraction) in the base DES solvent. By measuring their thermophysical properties, flow regime, and agglomeration behavior, NDDESs at a volume fraction of 0.005 were chosen as an optimum choice. Both the DESs and NDDESs were found to be of Newtonian in behavior at all temperatures of the measurement. The model prediction for viscosity agreed well with experimental values at a low volume fraction of nanoparticles. When compared to DESs, the enhancement in the viscosity of NDDES was 96% higher at a 0.005 volume fraction of nanoparticles. The thermal conductivity and heat capacity enhancement was 24% and 50% higher, respectively, at a 0.005 volume fraction of nanoparticles. Thereafter, forced convection experiments were carried out in the laminar regime. An appreciable increase in the coefficient of heat transfer was attributed to the increased thermophysical properties of DES nanofluids and a delay in the development of the boundary layer in the entrance areas. This behavior indicates that measures could be taken such as creating “artificial entrance” regions along a pipeline to maximize the performance of these novel nanofluids. In the penultimate section, numerical modeling using COMSOL was also carried out to validate the heat transfer coefficient and Nusselt number.

Computational Details

DESs are synthesized due to primary hydrogen bonds between a hydrogen bond donor (HBD) and a hydrogen bond acceptor (HBA). This renders a new chemical entity with a melting point lower than those of the initial compounds. It should also be noted that not all ratios of HBD and HBA will give us a eutectic point or a liquid phase. It is those points or, in other words, the lowest temperature that needs to be computed in such a manner that a liquid phase of DES coexist. This can be initiated through quantum chemical calculations and then adopting a statistical-based approach. Hence, the COSMO-SAC (conductor-like screening model–segment activity coefficient model) is adopted. The detailed methodology of COSMO and COSMO-SAC is already available in our earlier work.[38,39] The applications of COSMO-SAC are well known and documented in areas such as distillation, extraction, and absorption. Once the optimum ratio is known, we shall then proceed to the synthesis.

The procedure starts with the geometry optimization followed by COSMO-SAC predictions. The geometry optimization on all the structures was carried out using the density functional theory (DFT) B3LYP along the optimized structure with SDD basis set. The COSMO file was generated by the BVP86/TZVP/DFT level of theory.[38] Gaussian 09[40] was used to generate the above procedure or also termed as COSMO file initiation. The global adjustable parameters for generating the activity coefficient via a statistical mechanical framework were the surface area of the segment (aeff = 6.32 Å2), the misfit energy interaction constant [α′ = 8419 kcal Å4/(mol e2)], the cutoff for hydrogen-bonding interaction (σHB = 0.0084 e/Å2), and the hydrogen-bonding interaction constant [cHB = 75,006 kcal Å4/(mol e2)]. Thereafter, the mole fraction was predicted for both HBD and HBA by the activity coefficient in either phase at different temperatures (T) (eq )where γsolute, xsolute, ΔHf, and Tm are the activity coefficient, the mole fraction, the enthalpy of fusion, and the melting point, respectively. The solute here refers to dl-menthol (Figure ) as it has the lower boiling point. Figure shows the solid–liquid equilibrium diagram for mixtures of dl-menthol with oleic acid as a function of composition. It is found that a eutectic mixture of dl-menthol and oleic acid is formed at a molar ratio of 0.41:0.59 and a temperature of 270 K. Thus, based on the COSMO-SAC predictions of the eutectic point, the appropriate molar ratio of HBA/HBD is 0.59/0.41 = 1.4. This corresponds to the actual molar ratio of dl-menthol/oleic acid, respectively. However, we have adopted 1:1 as decreasing the mole fraction of menthol (Figure ) did not alter the liquid phase of the eutectic mixture. With the obtained ratio (i.e., 1:1), we shall now discuss the synthesis procedure in the ensuing section.

Figure 11

Structure of oleic acid and dl-menthol.

Figure 12

COSMO-SAC-predicted eutectic point of DESs.

Materials and Methods

Materials

dl-Menthol having a purity of 95% was purchased from Sigma-Aldrich (Figure ). Oleic acid having a purity of >90% was supplied by Otto Chemie Pvt. Ltd. (Figure ). Aluminum oxide (Al2O3) nanoparticles having a particle size of 50 nm as measured by TEM were bought from Sigma-Aldrich. DMSO-d6 was used as the NMR solvent and supplied by Merck (Germany). The chemicals were used without further purification. The densities of the chemicals were measured by an Anton Paar density meter (DMA 4500 M) for comparison with the manufacturer’s specification. The measured densities were within ±1%. The viscosities were also measured by an Anton Paar interfacial rheometer (Physica MCR301). The measured viscosities were of ±1% with literature values.

Experimental Details

Synthesis of DESs and NDDESs

To synthesize the DESs, an equimolar ratio of dl-menthol as HBA and oleic acid as HBD was taken. Both HBD and HBA were added to a flat-bottom flask, which was fitted with a reflux condenser. It was then kept for 12–24 h at 343.15 K with continuous stirring until a clear homogenous liquid was formed. The clear liquid or the DESs were then placed at room temperature (298.15 K) overnight. To confirm the composition of the DESs, 1H NMR (Figure ) were recorded and compared with the 1H NMR of the individual pure component. No new peaks were observed upon mixing the two, implying that there were no reactions between the starting materials. Further, the melting point of the synthesized DESs was measured as 266.15 K by differential scanning calorimetry (DSC1, Mettler Toledo, Germany), while the individual melting points of dl-menthol and oleic acid are 307.15 and 286.15 K, respectively. This also agrees well with the obtained melting point from COSMO-SAC predictions (270 K) as given in Figure .

Figure 13

1H NMR analysis of pure dl-menthol, oleic acid, and DESs.

To the synthesized DESs, an appropriate volume fraction of alumina nanoparticles (0.001, 0.005, 0.0075, and 0.01 vol %) was added, which gave us the NDDESs. Nanofluids having the nanoparticles were initially mixed through a vortex mixture (SPINIX MC-01, Tarsons). One of the primary objectives in the Al2O3 nanofluid is to obtain a homogenous and uniform suspension of nanoparticles. This usually occurs by the minimization of agglomerated nanoparticles. To prevent any possible agglomeration, ultrasonication (GT-1990QTS, ANTECH) was applied for 60 min to get a homogenous distribution of nanoparticles. To confirm the particle suspension behavior of the nanofluid, the zeta potential is considered to be an important parameter. The agglomeration of suspended particles primarily occurs due to the higher surface energy, which leads to precipitation. This was confirmed through the zeta potential measurement of nanofluids by Delsa Nano (Delsa Nano C, BECKMAN COULTER).

According to Vandsburger,[41] when the zeta potential is close to ±30 mV, the nanofluids are expected to be moderately stable. If the zeta potential is near ±45 mV, then the stability of nanofluids is guaranteed. The zeta potential value above ±60 mV illustrates an excellent stability of the nanofluid system. The zeta potential of 0.005 vol % Al2O3 nanofluid was found to be 96.51 mV, which indicates an excellent stability of nanofluid and is also likely to possess lower chances of settlement. It is a known fact that the suspension has a potential electrostatic stability due to the strong repulsive forces within the charged particles. This reduces the probability of coalescence, leading to a stable suspension in DESs. The stability of the nanoparticles was also analyzed by measuring the particle sizes using the dynamic light scattering (DLS) technique (Delsa Nano C, BECKMAN COULTER). The measurements were conducted for 1 week with six measurements taken each day. Further, each measurement was also performed in triplicate. The values obtained (±200 nm) are clearly higher than the nominal sizes as per the manufacturer’s specification (i.e., 70 nm). However, it should be noted that with the DLS technique, the obtained size is the hydrodynamic diameter, which inherently is the sum of the particle diameter and the Debye length. This explains a higher size than the real particle size. The Debye length is the measure of the charge carrier net electrostatic effect in solution or DESs. It is also termed as the thickness of the diffuse layer that moves with the alumina nanoparticle within the DES eutectic mixture. The behavior of the nanofluids was found to be similar, i.e., the particle size increased for a few hours after which time it was considered to remain stable. We did not observe sizes greater than ±200 nm. It suggests that the alumina nanoparticles in DESs agglomerate in a few hours and forms a complex with an internal structure where it then remains stable.

Measurement of Thermophysical Properties

To ascertain the thermal stability, TGA (TG209 F1, Libra, NETZSCH, Germany) was performed for both DESs and NDDESs under nitrogen atmosphere at a heating rate of 10 °C per minute. From the TGA data, it can be seen that the thermal stability of both DESs and NDDESs was almost similar and close to 110 °C for a 10% mass loss (Figure ). Thereafter, the measurement of thermophysical properties such as density, viscosity, thermal conductivity, and specific heat capacity[20,21] was conducted. While the heat capacity indicates the energy storage capacity of DESs and NDDESs in the CSP system, viscosity provides the required pumping power for both DESs and NDDESs. In a similar analogy, the thermal conductivity shall indicate heat conductance properties.

Figure 14

TGA analysis of DESs and NDDESs.

The densities of DESs and NDDESs were measured by the Anton Paar density meter (DMA 4500 M) in the temperature range of 293.15–423.15 K. The principle used for this measurement is the oscillating U-tube method. The sample was injected into the U-shaped borosilicate glass tube that oscillates at its characteristic frequency, which is directly related to the density of the sample. The viscosity of DES and NDDES was measured by the Anton Paar interfacial rheometer (Physica MCR301) as a function of temperature in the range of 298.15–423.15 K.

The thermal conductivities of both DESs and NDDESs were measured using a KD2 Pro thermal property analyzer (Decagon Device, USA). The principle of measurement is based on the hot-wire method. The device has a probe termed “KS-1” having dimensions of 60 mm in length and 1.3 mm in diameter, which was inserted vertically into the test sample. For controlling and conducting the measurements, the probe is connected to a microcontroller. The meter was calibrated with standard glycerin. A thermal bath was used to maintain the constant temperature of the measuring sample. The temperature accuracy of the bath was within ±273.18 K. The experiment was performed with a temperature range of 298.15–373.15 K. The heat capacity of both DESs and NDDESs was measured using a differential scanning calorimeter (DSC1, Mettler Toledo, Germany). The specific heat capacity was measured from 308.15 to 423.15 K.

Forced Convection Experimental Setup and Data Processing

Figure represents the schematic diagram of the forced convection setup used in this experiment. The setup comprises a test section, a magnetic pump, a rotameter, a storage tank, and a condenser. The test section is equipped with seven thermocouples and two pressure transducers. The pump (Taha PMD 15) was connected to a flow control valve followed by a rotameter (Apex 10LPM) to measure the flow rate. The test section was wrapped by flexible heating tape (Brisk Heat) to maintain a uniform heat flux throughout the test section. A DC power supply (GATTS MX1174A) ensured a power output to the heater. To lower the heat loss and attain a constant heat flux condition, fiberglass insulation was used for the entire test section. A total of five J-type thermocouples were inserted on the surface of the test section. Two more J-type thermocouples were welded at the inlet and outlet of the test section to measure the inlet and exit liquid temperatures. To measure the pressure drop along the test section, two pressure transducers were connected at the inlet and outlet. The material of construction of the test section was a stainless steel (SS-316) tube of 9 mm in inner diameter, 12 mm in outer diameter, and 1000 mm in length. All thermocouples (±2 °C) and pressure transducers (±0.2mV) were connected to a National Instrument (NI) data acquisition system (cDAQ-9178). It consisted of a temperature card (namely, NI 9211) and a pressure card (NI 9203), which were then interfaced with a computer. The LabVIEW software was used for data processing.

For a better experimental result, the entire test section was run by deionized water. After putting the DESs in the tank, the pump was started and the desired flow rate was maintained by a control valve and a rotameter. After reaching the steady state, the temperatures at designated points of the test section were recorded through the LabVIEW software. After recording the data, the flow rate was varied in an ascending manner. This was repeated up until the maximum flow rate of the pump was reached. Thereafter, the forced convection study of DESs and NDDESs at a volume fraction of 0.005 was performed. Figure displays the circular test section and the flow loop used in the heat transfer performance of DES and NDDES experiments. The experimental setup consists of an NDDES tank, a pump, a test section, a heat exchanger, a thermocouple, and a digital manometer. The test section used was as a circular stainless steel tube of 9 mm in inner diameter, 12 mm in outer diameter, and 1000 mm in length. A constant heat flux boundary condition was used. The heat flux (q) was measured from the heater input power (Q) and heating surface area (A) using the following equationwhere d0 is the tube outer diameter and l is the testing section (heating) length, while V and I are the input voltage and current, respectively. The local heat transfer coefficient along the test section, h(x), has been calculated using the following equationwhere Tw′(x) and Tf′(x) are the local temperatures of the inner surface and bulk liquid, respectively. The inner surface temperature was computed with the one-dimensional steady-state heat conduction equation having a constant heat flux boundary condition. The inner surface temperature is given belowwhere TW(x) is the local temperature of the outer surface as interfaced by the thermocouples, ro and ri are the outer and inner radius of the test tube, respectively, and ks is the thermal conductivity of the pipe. In a similar manner, the bulk mean temperature of the liquid can be computed from the energy balance relationwhere Tf is the liquid inlet temperature of the test section, Cp is the specific heat capacity of the liquid, and V′ is the volumetric flow rate. All fluid properties have been evaluated at the average temperature (Tav = (Tin + Tout)/2), i.e., the inlet and outlet fluid temperatures of the test section.

COMSOL Simulations

The development of flow through a pipe in the laminar flow regime is depicted in Figure . This has been used for the numerical modeling studies using COMSOL (version 5.2a). For COMSOL, the continuity equation is written in the vector form asThe equation of motion for an incompressible fluid in vector form is then written asThe first two terms on the left-hand side signify the inertia term, while the first term on the right-hand side represents the pressure gradient. The second term on the right-hand side represents the diffusion term, while the last term is the body force term. In a similar manner, the equation of energy takes the form as given below:The first two terms in the energy equation represents the accumulation term and convection term, respectively, while the last term is due to heat conduction. On a similar note, the first term on the right side of eq represents the heat source terms, while the second term denotes the viscous heat dissipation term.

Figure 16

Schematic of pipe flow in the laminar region.