**3. Synthesis and preparation of nanofluids**

**Figure 1.** Diverse particle shapes and geometries.

with that of conventional fluids, an idea to introduce conducting particles to fluids was considered. Among diverse particles geometry, different particle shapes occur naturally or are

Heat transfer using fluids is a very complicated phenomenon, and various factors such as fluid stability, composition, viscosity, surface charge, interface, and morphology of the dispersed nanostructures influence the observed results [3, 6, 46–59]. Optimization and high efficiency of components and devices have gained great importance since these factors play a crucial role in diverse fields. Solid materials such as metals, CNTs, oxide/nitride/carbide ceramics, semiconductors, and composite materials having higher thermal conductivity can be homogeneously suspended and stabilized within conventional fluids, resulting in better thermal transport performance composite fluids. Nevertheless, improvement in thermal conductivity cannot be achieved by just increasing the solid filler concentration because each system presents a threshold, in which beyond a certain limit, increasing the filler fraction will also increase

Most early studies used suspensions of millimeter or micrometer-sized particles, which led to countless problems, such as a tendency to rapidly sediment, unless flow rate is increased; not only losing the improvements in thermal conductivity, but also forming sludge sediments, increasing the thermal resistance and impairing the heat transfer capacity of the conventional fluids. Furthermore, fluids of this scale size could have considerably larger pressure drops [60–64], thus making flow through small channels much more difficult since diverse parameters are critical for device performance, such as morphology and stability of nanostructures, fluids composition, viscosity, fast sedimentation, channels clogging, erosion or wear, among others, which are often very serious for systems consisting of small channels [3, 65–69].

A revolution in the field of HTFs arose with the advent of nanofluids (NFs), a term introduced by Prof. Choi's research group in the late 1990s at Argonne National Lab [68]. The first inves-

O3

nanoparticles within water, and by

the viscosity, which will adversely affect the fluid properties and performance.

engineered for specific applications, as shown in **Figure 1**.

218 Microfluidics and Nanofluidics

tigations were performed by Masuda et al. [69] for Al2

The manipulation of matter on the nanometer scale has become a central focus from both fundamental and technological perspectives. Unique, unpredictable, and highly intriguing physical, electrical, mechanical, optical and magnetic phenomena result from the confinement of matter into nanoscale features. Morphology control in nanostructures has become a key issue in the preparation of electronic or mechanical nanodevices and functional materials [88]. A wide variety of combinations of nanostructures and conventional fluids can be used to synthesize and prepare stable nanofluids for diverse applications. Nanofluids could be manufactured by two methods. The first step method is a process in which, simultaneously, nanostructures are made and dispersed within the base fluid [89–91]. This method avoids diverse processes such as particles drying, storage, handling, and dispersion; so, the agglomeration of nanoparticles is minimized; therefore, stability of nanofluids is improved [89, 90]. In most experimental studies, nanofluids are synthesized in a two-step process [3, 6, 56, 92–96], which is a classic synthesis method of nanofluids. Various nanostructures such as nanofibers, nanotubes, nanosheets, among other nanomaterials used in this technique are initially produced by mechanical comminuting, chemical reaction, inner gas condensation or decomposition of organic complex [97–99] and finally obtained as dry powder. Then, it is followed by the second step in which the as-produced nanostructures are homogeneously dispersed into base conventional fluids through mechanical agitation (stirring) or ultrasonication [6, 97– 102]. Furthermore, this process is an economic method to produce nanofluids at large scale, since nanostructures synthesis techniques are readily scaled up to mass production levels. To obtain a good stability and homogeneous dispersion of nanostructures within a fluid, sonication process is used to speed dissolution by breaking intermolecular interactions. The main disadvantage of this method is that due to the high surface area and surface attractively, the nanostructures tend to agglomerate. The nanostructures agglomeration in the fluid results in decreasing the thermal conductivity performance and increasing the settlement and clogging of microchannels. Therefore, to reduce these effects, surfactants or additives are widely used to stabilize nanostructures within the fluids.

#### **3.1. Nanofluids: Variables and features**

The concept and strategies of this work have a significant departure from diverse investigations in thermal management applications. Even though there have been several investigations on HTFs with nanoparticles reinforcement, there is still a room for great opportunities to continue developments and understand the implications and effects of this technology. Diverse challenges regarding nanoparticles effect on thermal transport and energetic performance as well as nanofluids industrialization have been studied (**Figure 2**). The heat transfer enhancement in nanofluids has been attributed to many variables, which are presented in the following section.

*3.1.2. Nanofiller size*

the impact of Al2

O3

**Figure 3.** Schematic of Brownian motion of nanoparticles.

**Figure 2.** Common challenges of nanofluid developments.

Diverse studies have found that as nanostructures are reduced in size, the effective thermal conductivity of the nanofluid increases [13, 109–114]. As the nanoparticle size is reduced, Brownian motion is induced. Also, lighter and smaller nanoparticles are better at resisting sedimentation, one of the biggest technical challenges in experimenting with nanofluids [77].

ticle sizes of 36 and 47 nm at various filler fractions. The nanofluid with 36 nm particles improved the effective thermal conductivity enhancement at ~35°C, as varying the filler fraction from 0.5 vol.% up to 6.0 vol.% (~7% to ~28%, respectively). Agarwal et al. [115] presented

of kerosene-based nanofluid. Thermal conductivity increases from 1.3% to 9.3% over a particle filler fraction of 0.01 vol.% to 0.10 vol.%. Thermal conductivity performance and viscosity

O3

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221

size of nanoparticles on thermal conductivity and the dynamic viscosity

/DiW nanofluids with par-

Li and Peterson [109] investigated the thermal properties of Al2

#### *3.1.1. Brownian motion*

Researchers have found that Brownian motion, which is the random movement of particles (**Figure 3**), is a key mechanism for the anomalous increase in the heat transport of nanofluids [55, 78, 103–108]. Brownian motion tends to move the particles from higher concentration areas to the lower concentration areas. Research on fillers motion caused by temperature gradient was studied by Koo and Kleinstreuer [103]; it was shown that the Brownian motion has more impact on the thermal properties of nanofluids than to the effects of a temperature gradient. Aminfar and Motallebzadeh [108] investigated the concentration distribution and velocity field of nanoparticles on water/Al<sup>2</sup> O3 nanofluid in a pipe. It was observed that the Brownian forces have most impact on the nanoparticles filler fraction distribution and the velocity field when compared to other forces such as thermophoretic and gravitational forces. Brownian motion only exists when the particles within the fluid are extremely small and, as the size of the particles gets larger, Brownian motion effects are reduced.

**Figure 2.** Common challenges of nanofluid developments.

#### *3.1.2. Nanofiller size*

nanostructures are made and dispersed within the base fluid [89–91]. This method avoids diverse processes such as particles drying, storage, handling, and dispersion; so, the agglomeration of nanoparticles is minimized; therefore, stability of nanofluids is improved [89, 90]. In most experimental studies, nanofluids are synthesized in a two-step process [3, 6, 56, 92–96], which is a classic synthesis method of nanofluids. Various nanostructures such as nanofibers, nanotubes, nanosheets, among other nanomaterials used in this technique are initially produced by mechanical comminuting, chemical reaction, inner gas condensation or decomposition of organic complex [97–99] and finally obtained as dry powder. Then, it is followed by the second step in which the as-produced nanostructures are homogeneously dispersed into base conventional fluids through mechanical agitation (stirring) or ultrasonication [6, 97– 102]. Furthermore, this process is an economic method to produce nanofluids at large scale, since nanostructures synthesis techniques are readily scaled up to mass production levels. To obtain a good stability and homogeneous dispersion of nanostructures within a fluid, sonication process is used to speed dissolution by breaking intermolecular interactions. The main disadvantage of this method is that due to the high surface area and surface attractively, the nanostructures tend to agglomerate. The nanostructures agglomeration in the fluid results in decreasing the thermal conductivity performance and increasing the settlement and clogging of microchannels. Therefore, to reduce these effects, surfactants or additives are widely used

The concept and strategies of this work have a significant departure from diverse investigations in thermal management applications. Even though there have been several investigations on HTFs with nanoparticles reinforcement, there is still a room for great opportunities to continue developments and understand the implications and effects of this technology. Diverse challenges regarding nanoparticles effect on thermal transport and energetic performance as well as nanofluids industrialization have been studied (**Figure 2**). The heat transfer enhancement in nanofluids has been attributed to many variables, which are presented in the

Researchers have found that Brownian motion, which is the random movement of particles (**Figure 3**), is a key mechanism for the anomalous increase in the heat transport of nanofluids [55, 78, 103–108]. Brownian motion tends to move the particles from higher concentration areas to the lower concentration areas. Research on fillers motion caused by temperature gradient was studied by Koo and Kleinstreuer [103]; it was shown that the Brownian motion has more impact on the thermal properties of nanofluids than to the effects of a temperature gradient. Aminfar and Motallebzadeh [108] investigated the concentration distribution and

O3

the size of the particles gets larger, Brownian motion effects are reduced.

Brownian forces have most impact on the nanoparticles filler fraction distribution and the velocity field when compared to other forces such as thermophoretic and gravitational forces. Brownian motion only exists when the particles within the fluid are extremely small and, as

nanofluid in a pipe. It was observed that the

to stabilize nanostructures within the fluids.

velocity field of nanoparticles on water/Al<sup>2</sup>

**3.1. Nanofluids: Variables and features**

following section.

220 Microfluidics and Nanofluidics

*3.1.1. Brownian motion*

Diverse studies have found that as nanostructures are reduced in size, the effective thermal conductivity of the nanofluid increases [13, 109–114]. As the nanoparticle size is reduced, Brownian motion is induced. Also, lighter and smaller nanoparticles are better at resisting sedimentation, one of the biggest technical challenges in experimenting with nanofluids [77]. Li and Peterson [109] investigated the thermal properties of Al2 O3 /DiW nanofluids with particle sizes of 36 and 47 nm at various filler fractions. The nanofluid with 36 nm particles improved the effective thermal conductivity enhancement at ~35°C, as varying the filler fraction from 0.5 vol.% up to 6.0 vol.% (~7% to ~28%, respectively). Agarwal et al. [115] presented the impact of Al2 O3 size of nanoparticles on thermal conductivity and the dynamic viscosity of kerosene-based nanofluid. Thermal conductivity increases from 1.3% to 9.3% over a particle filler fraction of 0.01 vol.% to 0.10 vol.%. Thermal conductivity performance and viscosity

**Figure 3.** Schematic of Brownian motion of nanoparticles.

were found to be higher for smaller size nanoparticles compared to larger size. At 0.50 vol.%, nanofluid with 13 nm particle size displays 22% improvement in the effective thermal conductivity, compared to only 17% for 50 nm. Beck et al. [116] investigated Al2 O3 /water nanofluids with diverse particle sizes ranging from 8 nm to ~300 nm in diameter; the thermal conductivity enhancement decreases as the particle size decreases below ~50 nm. This behavior was attributed to nanoparticles thermal conductivity, as the particle size becomes small enough to be affected by increased phonon scattering [116]. Teng et al. [112] studied on the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of Al2 O3 /water nanofluid with filler fraction up to 2.0 wt.% and different Al<sup>2</sup> O3 particle nominal diameters. The results showed a dependence relationship between high thermal conductivity ratios and enhanced sensitivity, and small nanoparticle size and higher temperature. Nguyen et al. [117] studied the heat transfer enhancement and behavior of Al<sup>2</sup> O3 /water nanofluid for microprocessors/electronic purposes. It is found that with smaller nanoparticles (36 nm in diameter), nanofluids showed higher convective heat transfer coefficients than with larger ones (47 nm in diameter). From Nguyen's research, thermal transport increased 40% at 6.8 vol.% filler fraction, as compared to water. He et al. [118] studied the heat transfer behavior of TiO<sup>2</sup> water nanofluids with diameters of 95 nm, 145 nm and 210 nm at various filler fractions. For the 95 nm particle size nanofluid, the thermal conductivity showed an increase from 1% to ~5% at 1.0 wt.% and 4.9 wt.%, respectively, compared to water; as filler fraction increased, the thermal conductivity increased as well. It was shown that the effective thermal conductivity decreases as particle size increases. On the other research, Żyła et al. [119] studied the effects of TiN nanoparticles within EG at two different particles size, 20 and 50 nm. It was concluded that the increase in nanoparticle filler fraction led to similar trends for nanofluids properties. At same content, thermal conductivity and surface tension of nanofluids are higher with smaller nanoparticles. Esfahani et al. [120] observed that thermal conductivity of graphene oxide (GO) NFs depends on both particle-size distribution of GO and viscosity of GO NFs. In their work, GO NFs showed enhanced thermal conductivity performance as compared to base water.

The nanostructure size effect is apparently due to interlaying mechanism, van der Waals forces and the micromotions of nanoparticles are stronger when containing lower-sized nanostructures; and the interactions between nanoparticles and fluids are more severe, which results in a stronger energy transmission and a higher thermal transport process in nanofluids. The smaller the particle size, the higher will be the improvement due to the high surface area observed. This trend is observed by most researchers and is supported by two mechanisms: Brownian motion and liquid layering around nanostructures. Hence, nanofillers size is a determinant variable for heat transfer nanofluids, since, as previously stated, its smaller

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223

Particle geometry is an important parameter to be considered since it has critical effects on nanofluids performance. There have been several efforts to understand the effects of nanoparticles shape regarding the thermal transport phenomena. It has been observed by several studies that rod-shaped nanoparticles, such as CNTs, remove more heat than spherical nanoparticles [134–139]; this is most probably due to rod-shaped particles' larger aspect ratio (ratio between a particle's surface area to volume) than spherical nanoparticles. For instance, Elias et al. [134] studied various boehmite alumina (γ-AlOOH) nanoparticle shapes (spherical, cylindrical, blades, bricks and platelets) dispersed within EG/water mixtures. The best performance was achieved by the cylindrical-shaped nanoreinforced fluid, followed by bricks, blades, platelets and spherical-shaped nanoparticles, respectively. Thermal conductivity enhancement of cylindrical shape nanoparticles is observed to be ~3% higher than the spherical shape at 1.0 vol.% concentration. On similar study, Kim et al. [140] investigated the effects of particle shape on suspension stability and thermal transport performance of water-based boehmite alumina nanofluids. The thermal conductivities of nanofluids with blade, brick and platelet shaped

particles are maximally enhanced up to 16, 28, and 23% at 7.0 vol.%, respectively.

From various studies, it can be concluded that the rod-shaped nanostructures possess higher thermal conductivity performance compared to spherical shape nanoparticles due to larger surface area and rapid heat transport along relatively long distances due to the greater length, usually of the order of micrometers. However, there is some contradiction observed based on studies performed by Xie et al. [141], where thermal conductivity enhancement using spherical (26 nm average) and cylindrical (600 nm average)-shaped SiC nanoparticles suspended within water were evaluated. An enhancement of ~23% at 4.0 vol.% for cylindrical particles was observed, but only 16% increase at 4.2 vol.% for spherical particles was reported. Results showed higher enhancement at larger particle size. These contradictions with other literature could be explained by the severe clustering of nanoparticles having smaller particle size. Although at a certain level clustering may enhance the thermal conductivity, excessive clustering may create an opposite effect, resulting in the sedimentation of nanoparticles [142]. Sudarsana Reddy and Chamkha[139] studied the effects of shape on nanoparticles on natural convection magnetohydrodynamic (MHD) fluids. Results reveal that significant heat transfer enhancement is noticed as the size of nanoparticles decreases. Moreover, the type of the nanoparticles and the type of the base fluid (water/kerosene) also influenced the natural

size reduces or avoids critical issues of larger fillers.

*3.1.3. Particle shape/surface area*

There have been a few reports on SiC, CeO<sup>2</sup> , and SiO<sup>2</sup> nanoparticles reinforcing conventional fluids that stated a decrease of the effective thermal conductivity with increase in particle size [47, 121–132]. Beck et al. performed studies on water-based ceria (CeO<sup>2</sup> ) nanofluids [123], which showed an increase in the effective thermal conductivity with an increase of nanoparticle size, although only two particle sizes were studied (12 nm and 74 nm). Silica-ethanol nanofluid was investigated by Hossein Karimi Darvanjooghi and Nasr Esfahany [132] over various particle sizes, temperatures and filler fractions. It was observed that with the increase in particle size and temperature, the thermal conductivity performance of silica–ethanol nanofluid increases for all the investigated filler fractions. 2D nanostructures have also been recently studied; Taha-Tijerina et al. developed a novel nanofluid by adding only 0.10 wt.% of exfoliated hexagonal boron nitride (h-BN) 2D-nanosheets within mineral oil (MO) [30]. Enhancement in thermal conductivity for 0.10 wt.% h-BN/MO nanofluid was more than 75% in comparison with MO. Similarly, Mehrali et al. [133] investigated the effects on thermal transport of graphene-based nanofluids. It was found that at 4.0 vol.%, a significant thermal conductivity enhancement of ~45% was obtained.

The nanostructure size effect is apparently due to interlaying mechanism, van der Waals forces and the micromotions of nanoparticles are stronger when containing lower-sized nanostructures; and the interactions between nanoparticles and fluids are more severe, which results in a stronger energy transmission and a higher thermal transport process in nanofluids. The smaller the particle size, the higher will be the improvement due to the high surface area observed. This trend is observed by most researchers and is supported by two mechanisms: Brownian motion and liquid layering around nanostructures. Hence, nanofillers size is a determinant variable for heat transfer nanofluids, since, as previously stated, its smaller size reduces or avoids critical issues of larger fillers.

#### *3.1.3. Particle shape/surface area*

were found to be higher for smaller size nanoparticles compared to larger size. At 0.50 vol.%, nanofluid with 13 nm particle size displays 22% improvement in the effective thermal con-

fluids with diverse particle sizes ranging from 8 nm to ~300 nm in diameter; the thermal conductivity enhancement decreases as the particle size decreases below ~50 nm. This behavior was attributed to nanoparticles thermal conductivity, as the particle size becomes small enough to be affected by increased phonon scattering [116]. Teng et al. [112] studied on the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of

diameters. The results showed a dependence relationship between high thermal conductivity ratios and enhanced sensitivity, and small nanoparticle size and higher temperature.

fluid for microprocessors/electronic purposes. It is found that with smaller nanoparticles (36 nm in diameter), nanofluids showed higher convective heat transfer coefficients than with larger ones (47 nm in diameter). From Nguyen's research, thermal transport increased 40% at 6.8 vol.% filler fraction, as compared to water. He et al. [118] studied the heat transfer

filler fractions. For the 95 nm particle size nanofluid, the thermal conductivity showed an increase from 1% to ~5% at 1.0 wt.% and 4.9 wt.%, respectively, compared to water; as filler fraction increased, the thermal conductivity increased as well. It was shown that the effective thermal conductivity decreases as particle size increases. On the other research, Żyła et al. [119] studied the effects of TiN nanoparticles within EG at two different particles size, 20 and 50 nm. It was concluded that the increase in nanoparticle filler fraction led to similar trends for nanofluids properties. At same content, thermal conductivity and surface tension of nanofluids are higher with smaller nanoparticles. Esfahani et al. [120] observed that thermal conductivity of graphene oxide (GO) NFs depends on both particle-size distribution of GO and viscosity of GO NFs. In their work, GO NFs showed enhanced thermal conductivity

, and SiO<sup>2</sup>

fluids that stated a decrease of the effective thermal conductivity with increase in particle

which showed an increase in the effective thermal conductivity with an increase of nanoparticle size, although only two particle sizes were studied (12 nm and 74 nm). Silica-ethanol nanofluid was investigated by Hossein Karimi Darvanjooghi and Nasr Esfahany [132] over various particle sizes, temperatures and filler fractions. It was observed that with the increase in particle size and temperature, the thermal conductivity performance of silica–ethanol nanofluid increases for all the investigated filler fractions. 2D nanostructures have also been recently studied; Taha-Tijerina et al. developed a novel nanofluid by adding only 0.10 wt.% of exfoliated hexagonal boron nitride (h-BN) 2D-nanosheets within mineral oil (MO) [30]. Enhancement in thermal conductivity for 0.10 wt.% h-BN/MO nanofluid was more than 75% in comparison with MO. Similarly, Mehrali et al. [133] investigated the effects on thermal transport of graphene-based nanofluids. It was found that at 4.0 vol.%, a significant thermal

size [47, 121–132]. Beck et al. performed studies on water-based ceria (CeO<sup>2</sup>

water nanofluids with diameters of 95 nm, 145 nm and 210 nm at various

O3

O3

O3

nanoparticles reinforcing conventional

) nanofluids [123],

/water nano-

particle nominal

/water nano-

ductivity, compared to only 17% for 50 nm. Beck et al. [116] investigated Al2

/water nanofluid with filler fraction up to 2.0 wt.% and different Al<sup>2</sup>

Nguyen et al. [117] studied the heat transfer enhancement and behavior of Al<sup>2</sup>

Al2 O3

behavior of TiO<sup>2</sup>

222 Microfluidics and Nanofluidics

performance as compared to base water.

There have been a few reports on SiC, CeO<sup>2</sup>

conductivity enhancement of ~45% was obtained.

Particle geometry is an important parameter to be considered since it has critical effects on nanofluids performance. There have been several efforts to understand the effects of nanoparticles shape regarding the thermal transport phenomena. It has been observed by several studies that rod-shaped nanoparticles, such as CNTs, remove more heat than spherical nanoparticles [134–139]; this is most probably due to rod-shaped particles' larger aspect ratio (ratio between a particle's surface area to volume) than spherical nanoparticles. For instance, Elias et al. [134] studied various boehmite alumina (γ-AlOOH) nanoparticle shapes (spherical, cylindrical, blades, bricks and platelets) dispersed within EG/water mixtures. The best performance was achieved by the cylindrical-shaped nanoreinforced fluid, followed by bricks, blades, platelets and spherical-shaped nanoparticles, respectively. Thermal conductivity enhancement of cylindrical shape nanoparticles is observed to be ~3% higher than the spherical shape at 1.0 vol.% concentration. On similar study, Kim et al. [140] investigated the effects of particle shape on suspension stability and thermal transport performance of water-based boehmite alumina nanofluids. The thermal conductivities of nanofluids with blade, brick and platelet shaped particles are maximally enhanced up to 16, 28, and 23% at 7.0 vol.%, respectively.

From various studies, it can be concluded that the rod-shaped nanostructures possess higher thermal conductivity performance compared to spherical shape nanoparticles due to larger surface area and rapid heat transport along relatively long distances due to the greater length, usually of the order of micrometers. However, there is some contradiction observed based on studies performed by Xie et al. [141], where thermal conductivity enhancement using spherical (26 nm average) and cylindrical (600 nm average)-shaped SiC nanoparticles suspended within water were evaluated. An enhancement of ~23% at 4.0 vol.% for cylindrical particles was observed, but only 16% increase at 4.2 vol.% for spherical particles was reported. Results showed higher enhancement at larger particle size. These contradictions with other literature could be explained by the severe clustering of nanoparticles having smaller particle size. Although at a certain level clustering may enhance the thermal conductivity, excessive clustering may create an opposite effect, resulting in the sedimentation of nanoparticles [142]. Sudarsana Reddy and Chamkha[139] studied the effects of shape on nanoparticles on natural convection magnetohydrodynamic (MHD) fluids. Results reveal that significant heat transfer enhancement is noticed as the size of nanoparticles decreases. Moreover, the type of the nanoparticles and the type of the base fluid (water/kerosene) also influenced the natural convection heat transfer. In another study, Aaiza et al. [143] investigated energy transport in MHD nanofluids with different nanoparticles shapes such as cylinders, platelets, blades, and bricks. It was observed that elongated structures such as cylinders and platelets result in higher viscosity at the same filler fraction due to structural limitation of rotational and transitional Brownian motion, which resulted in effects on thermal conductivity.

filler fraction (up to a threshold-optimum value). It was observed that the increase in particle concentration also increases the fluid viscosity, which should result in an increase in the boundary layer thickness, which overcomes the convective heat transfer coefficient as well. However, significant improvements in thermal conductivity are shown. For instance, at 40°C, the thermal conductivity improvements were significant: 7, 11, 13, 16 and 21% at 0.5, 1.0, 1.5, 2.0 and 3.0 vol.%, respectively. Research by Paul et al. [155] demonstrated that the thermal conductivity of water-based SiC nanofluids could be improved by 12% at only 0.1 vol.%. Studies on mixtures of water and EG-based SiC nanofluids were performed by Timofeeva et al. [121, 156], where nanofluids displayed 1.5–20% thermal conductivity enhancement at different filler fraction and nanoparticle sizes. Ferrouillat et al. [157] estimated that heat

improvement of 10–60% compared to pure water. Lee et al. [158] investigated the thermal conductivity of DI-water-based SiC nanofluids; a ~7% improvement was observed, compared to pure DI-water. Li and Zou [159] prepared homogeneous and stable nanofluids by dispersing SiC nanoparticles within mixtures of ethylene glycol and water. It was observed that thermal conductivity of water/EG-based SiC nanofluids increased with SiC concentrations. Improvements of ~34% at 1.0 vol.% of SiC were achieved. Pang et al. [153] studied the effect

 nanoparticles within methanol at various concentrations (0.01, 0.10 and 0.50 vol.%). Thermal conductivity enhancements were 6, 11 and ~16%, respectively, as compared to pure

A key challenge with nanofluids is that nanoparticles tend to agglomerate due to molecular interactions, such as van der Waals forces [122, 160]. The agglomeration of nanoparticles results not only in the settlement and clogging of microchannels, but also causes the effective surface area to volume ratio to decrease, which impacts the thermal conductivity performance of nanofluids. Nanoparticles agglomeration increases as filler fraction increases, due to closer particles and higher Van der Waals attraction. Similarly, this issue generates other

/water nanofluid in the particle ranges from 5 wt.% to 34 wt.%, and found an

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transfer of SiO2

of SiO2

fluid.

*3.1.5. Stability/particles agglomeration*

problems such as viscosity increments (**Figure 4**).

**Figure 4.** Scheme of nanoparticles sedimentation over time.
