**3. Synthesis and preparation of nanofluids**

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, mechanical, optical, electrical, 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 [72]. 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:

**(a)** *One-step method*: The one-step process simultaneously makes and disperses the nano‐ structures within the base fluid. 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 [73]. Thus, it is possible to obtain uniformly dispersed and highly stable suspended nanostructures within the base fluids [74, 75].

**(b)** *Two-step method*: Two-step method is the most widely used method for preparing nanofluids [15, 49, 76–82]. Various nanostructures such as nanofibers, nanotubes, nano‐ sheets, among other nanomaterials used in this technique are initially produced by mechanical comminuting, chemical reaction, vapor condensation, or decomposition of organic complex [83–85] and finally obtained as dry powder. Then, it is followed by further dispersion of as-produced nanostructures within base fluids through magnetic force agitation (stirring), ball milling, ultrasonic agitation, and high-shear mixing, among others [77, 81, 86, 87]. This procedure is the most economic method to produce nanofluids in large scale since nanoparticle synthesis techniques are readily scaled up to mass production levels. Sonication is used to speed dissolution by breaking intermolecular interactions, and homogeneously dispersing nanoparticles within a fluid. It is especially useful when it is not possible or difficult to stir a sample.

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

Therefore, one of the main advantages of nanofluids is that they can be specially engineered to optimally fulfill particular objectives, such as enhanced thermal conductivity, a higher thermal energy storage capacity, a higher heat transfer coefficients, a better temperature stabilization, and less pressure drop, among others. Moreover, nanofluids are promising for practical application without clogging, sediment or such. Nanofluids will keep the fluidic properties of the conventional fluids, behave almost like conventional fluids, and incur in little or no extra penalty of pressure drop (i.e., the viscosity increase is small) due to the fact that dispersed nanoparticles are extremely small, which are very stably suspended in fluids with or without the aid of additives or surfactants [55]. Hence, search for new nanofillers which can

It has been demonstrated that nanofluids for heat transfer applications have provided better thermal performance than conventional fluids [12, 15, 48, 49, 56–58]. Therefore, the advent of nanofluid-based heat transfer systems can make compact designs with highly efficient thermal,

Experiments on convection heat transfer of nanofluids were conducted by several research groups [57, 59–61]. The results showed significant improvements in heat transfer rates of nanofluids. Meanwhile, the thermal conductivity enhancement of nanofluids shows a tem‐ perature-dependent characteristic—increase of enhancement with rising temperature, which makes the nanofluids more suitable for applications at elevated temperatures [15, 49, 62–66]. Additionally, previous research has shown that nanofluids display better performance in their thermo-physical and tribology properties, such as thermal conductivity, thermal diffusivity, viscosity, friction, etc., compared to conventional fluids [15, 46–49, 67–71]. Hence, nanofluids could be used for aforesaid engineering applications. From all these, a great variety of nanocomposite materials have been developed, using diverse techniques and methodologies,

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, mechanical, optical, electrical, 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 [72]. 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

**(a)** *One-step method*: The one-step process simultaneously makes and disperses the nano‐ structures within the base fluid. 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 [73]. Thus, it is possible to obtain

get high thermal conductivities at lower filler fractions is important [15, 56].

physical, and electrical performance for instruments and devices.

158 Two-dimensional Materials - Synthesis, Characterization and Potential Applications

obtaining significant performance.

manufactured by two methods:

**3. Synthesis and preparation of nanofluids**

Diverse features and challenges regarding the effect of nanoparticles on thermal transport, tribological performance, and energetic performance have been studied. The heat transfer enhancement in nanofluids, for example, has been attributed to many variables including nanoparticle size, shape, and filler fraction. However, as mentioned, diverse challenges have hindered their large-scale applications (**Figure 3**), such as nanoparticle dispersion, agglomer‐ ation, long-term stability, increase in nanofluid viscosity, cost increase, and scale-up capacity for industrial applications, which are presented in the following sections.

**Figure 3.** Common challenges of nanofluid developments.

#### *3.1.1. Nanofiller size*

Diverse studies have found that as nanoparticles are reduced in size, the effective thermal conductivity of the nanofluid increases [13, 64, 88–94]. 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 [61]. Li et al. [88] investigated the thermal properties of Al2O3/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, varying the filler fractions from 0.5 to 6.0 vol.% (∼7 to ∼28%, respectively). Similar trend was observed for the nanofluid with 47 nm particles, but slightly lower thermal conductivity enhancement was shown compared to the smaller particles nanofluid (∼4 to ∼25%, respectively). Nguyen et al. [95] and Minsta et al. [89] studied the heat transfer enhancement and behavior of Al2O3-water nanofluid for microproc‐ essors/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. Chopkar et al. [96] studied 0.20–2.0 vol.% Al70Cu30 nanoparticle reinforced EG, and also found that thermal conductivity strongly depends on the size of nanoparticles.

He et al. [97] studied the heat transfer behavior of TiO2-water nanofluids with diameters of 95, 145, 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 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. Research conducted by Hong et al. [77] achieved 18% increase in thermal conductivity with only 0.55 vol.% of Fenanoparticles (∼10 nm size)-reinforced EG nanofluids. Showing as well that sonication of the nanofluid has an important effect on the thermal conductivity of the system indirectly proves the effect of particle size on the thermal conductivity of the nanofluid. Teng et al. [92] studied the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of Al2O3/water nanofluid with filler fraction up to 2.0 wt.%, and different Al2O3 particle nominal diameters (20, 50, and 100 nm). The results showed a dependence relationship between high thermal conductivity ratios and enhanced sensitivity, small nanoparticle size, and higher temperature. 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.

Nevertheless, there have been a few reports on SiC, CeO2, and Al2O3 nanoparticles reinforcing water that stated a decrease of the effective thermal conductivity with increase in particle size [98–101]. As shown by Beck et al.'s [100] research on Al2O3/water nanofluids with diverse particle sizes ranging from 8 to ∼300 nm in diameter, the thermal conductivity enhancement decreases as the particle size decreases below ∼50 nm. Beck et al. attribute this behavior to nanoparticles thermal conductivity, as the particle size becomes small enough to be affected by increased phonon scattering [100]. Similarly, studies performed on water-based CeO2 nanofluids [101] showed an increase in the effective thermal conductivity with an increase of nanoparticle size, although only two particle sizes were studied (12 and 74 nm).

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

*3.1.1. Nanofiller size*

nanoparticles.

fillers.

Diverse studies have found that as nanoparticles are reduced in size, the effective thermal conductivity of the nanofluid increases [13, 64, 88–94]. 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 [61]. Li et al. [88] investigated the thermal properties of Al2O3/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, varying the filler fractions from 0.5 to 6.0 vol.% (∼7 to ∼28%, respectively). Similar trend was observed for the nanofluid with 47 nm particles, but slightly lower thermal conductivity enhancement was shown compared to the smaller particles nanofluid (∼4 to ∼25%, respectively). Nguyen et al. [95] and Minsta et al. [89] studied the heat transfer enhancement and behavior of Al2O3-water nanofluid for microproc‐ essors/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. Chopkar et al. [96] studied 0.20–2.0 vol.% Al70Cu30 nanoparticle reinforced EG, and also found that thermal conductivity strongly depends on the size of

160 Two-dimensional Materials - Synthesis, Characterization and Potential Applications

He et al. [97] studied the heat transfer behavior of TiO2-water nanofluids with diameters of 95, 145, 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 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. Research conducted by Hong et al. [77] achieved 18% increase in thermal conductivity with only 0.55 vol.% of Fenanoparticles (∼10 nm size)-reinforced EG nanofluids. Showing as well that sonication of the nanofluid has an important effect on the thermal conductivity of the system indirectly proves the effect of particle size on the thermal conductivity of the nanofluid. Teng et al. [92] studied the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of Al2O3/water nanofluid with filler fraction up to 2.0 wt.%, and different Al2O3 particle nominal diameters (20, 50, and 100 nm). The results showed a dependence relationship between high thermal conductivity ratios and enhanced sensitivity, small nanoparticle size, and higher temperature. 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

Nevertheless, there have been a few reports on SiC, CeO2, and Al2O3 nanoparticles reinforcing water that stated a decrease of the effective thermal conductivity with increase in particle size [98–101]. As shown by Beck et al.'s [100] research on Al2O3/water nanofluids with diverse particle sizes ranging from 8 to ∼300 nm in diameter, the thermal conductivity enhancement decreases as the particle size decreases below ∼50 nm. Beck et al. attribute this behavior to nanoparticles thermal conductivity, as the particle size becomes small enough to be affected by increased phonon scattering [100]. Similarly, studies performed on water-based CeO2 Several studies have found that rod-shaped nanoparticles, such as CNTs, remove more heat than spherical nanoparticles [78, 102–107], probably because rod-shaped particles have a larger aspect ratio (the ratio between a particle's surface area to volume) than spherical nanoparticles. Elias et al. [103] studied various boehmite alumina (γ-AlOOH) nanoparticle shapes (cylindri‐ cal, spherical, bricks, blades, and platelets) within EG/water (50/50%). Nanofluids at diverse filler fraction, up to 1.0 vol.%, showed a linear increase in thermal conductivity. Best perform‐ ance was found for cylindrical-shaped nanoparticles, followed by bricks, blades, platelets, and spherical-shaped nanoparticles, respectively. Thermal conductivity enhancement of cylindri‐ cal-shaped nanoparticles is observed to be ∼2.5% higher than the spherical shape with 1.0 vol. % filler fraction. Murshed et al. [104] investigated water reinforced with TiO2 rod-type (10 nm in diameter and 40 nm in length) and spherical (15 nm) nanoparticles; an enhancement of thermal conductivity of ∼30 and ∼33%, respectively, was observed at 5.0 vol.% filler fraction compared to base fluid. EG-based nanofluids with addition of SiC nanowhiskers (1.5 μm in diameter and 18 μm in length) and spherical particles (diameter <40 μm) were investigated by Cherkasova et al. [106]. Nanowhiskers were prepared at various aspect ratios by ball milling from 0, 4, 12, and up to 28 h. At 2.5 vol.%, the thermal conductivity enhancement is observed to increase from 16.5 to 39.5% as the aspect ratio increases from 4.8 to 9.6. It is also observed that suspensions containing cylindrical particles showed significantly higher increase in thermal conductivity than suspensions with dispersed spherical particles. For 5.0 vol.%, a thermal conductivity enhancement of ∼85 and ∼20% was observed for suspensions containing SiC whiskers and spheres, respectively. Thermal conductivity increase for both types of particles is nearly linear with volume fraction of solids up to 5.0 vol.% as well. On other research on rod-type nanoparticles, Glory et al. [105] studied multiwall nanotubes (MWCNTs)/water nanofluids. An increase in thermal conductivity enhancement was observed with an increase of nanotube length. For instance, the relative increase of thermal conductivity of nanofluids at 2.0 wt.% with nanotubes with length of ∼0.5 μm was ∼14%, an 18% increase was observed for nanotubes with length of 1.0 μm, a 38% increase was observed for nanotubes with length of 1.7 μm, and finally, a ∼45% increase was observed for the longest nanotubes tested with length of ∼5.0 μm. As explained by Glory et al., this behavior is attributed to a mechanism where longer nanotubes diminish the number of nanotube-nanotube contacts, therefore favoring phonon transmission in the suspensions, giving an increase of the thermal conductivity. Other nanoparticles with morphology possessing large surface area are the 2D nanosheets, which are obtained by exfoliation layers in its structure [15, 108]. Moreover, little research has been conducted for 2D-nanoparticles reinforcing conventional fluids. Recently, it has been demon‐ strated by Taha-Tijerina et al. [15, 49] that 2D-based nanofluids have high impact in the thermal transport, as well as in physical, electrical, and tribological properties.

#### *3.1.3. Filler fraction*

Probably, the key variable for nanofluids' improvement is the nanofillers concentration homogeneously dispersed within conventional fluids. Filler fraction has been stated by volume and weight percentages in papers, patents, and reports. Effective thermal conductivity (*k*eff) and coefficient of friction (COF), among other properties of nanofluids improve with increas‐ ing nanoparticles filler fraction [109], but as the nanoparticles filler fraction increases, it may no longer be valid to assume a well-suspended nanoparticles. Also, pressure drop has been observed in diverse conventional fluids as filler fraction of different nanoparticles is increased [10]. This is why it is more effective to use a very small filler fraction in nanofluids [15, 110– 113]. At low filler fractions, nanostructures have more intense Brownian motion at higher temperatures, which can significantly enhance the effective thermal conductivity. But at high volume fractions, nanoparticles have high potential to be agglomerated at high temperatures.

#### *3.1.4. Particles agglomeration*

A key challenge with nanofluids is that nanoparticles tend to agglomerate due to molecular interactions, such as Van der Waals forces [99, 114]. Agglomeration of nanoparticles increases as filler fraction increases, due to closer particles and higher Van der Waals attraction. Similarly, this issue generates other problems such as viscosity increments (**Figure 4**). Ag‐ glomeration causes the effective surface area to volume ratio to decrease, which impacts the thermal conductivity performance of the fluid. Timofeeva et al. [99, 107] studied the thermal conductivity and viscosity of Al2O3 nanoparticles dispersed in water and EG. It is observed that the main parameters for controlling nanofluids' thermal conductivity enhancement are the geometry, agglomeration state, and surface resistance of nanoparticles. Karthikeyan et al. [109] identified that CuO nanoparticles and cluster size have a significant influence on thermal conductivity of water and EG. Similarly, it is found that nanoparticle agglomeration is time dependent; as time elapsed, agglomeration increased, which decreased the thermal conduc‐ tivity. Wang et al. [115] performed studies on diverse fluids (water, pump fluid, engine oil, and EG) with the addition of Al2O3 and CuO with 28 and 23 nm in diameter, respectively. Viscosity of these systems increase as nanoparticles agglomerate, also thermal conductivity performance is observed to decrease, most probably an effect of the agglomeration of the nanoparticles. Moreover, particle agglomeration is exacerbated by the size of the reinforced fillers. Nasiri et al. observed a reduction in thermal conductivity with time for water-based CNT nanofluids due to agglomeration [114]. However, some reports show that aggregation in water-based Al2O3 nanofluids significantly increases the thermal conductivity of the fluid [116, 117]. In other studies, stable nanofluids showed no significant variation in thermal conduc‐ tivity with time. Yu et al. observed that the thermal conductivity of EG-based ZnO nanofluids [118] and kerosene-based Fe3O4 nanofluids [119] were independent of time. Additionally, engine coolant-based Al2O3 nanofluid exhibited minimum change of thermal conductivity with time [120]. Yu et al. [121] conducted studies on EG-based graphene oxide nanosheets (GON). An enhancement in thermal conductivity at 5.0 vol.% of ∼61% was observed. Thermal conductivity performance was invariable for ∼7 days, reflecting high stability of GON/EG nanofluids.

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

#### *3.1.5. Stability*

*3.1.3. Filler fraction*

*3.1.4. Particles agglomeration*

nanofluids.

Probably, the key variable for nanofluids' improvement is the nanofillers concentration homogeneously dispersed within conventional fluids. Filler fraction has been stated by volume and weight percentages in papers, patents, and reports. Effective thermal conductivity (*k*eff) and coefficient of friction (COF), among other properties of nanofluids improve with increas‐ ing nanoparticles filler fraction [109], but as the nanoparticles filler fraction increases, it may no longer be valid to assume a well-suspended nanoparticles. Also, pressure drop has been observed in diverse conventional fluids as filler fraction of different nanoparticles is increased [10]. This is why it is more effective to use a very small filler fraction in nanofluids [15, 110– 113]. At low filler fractions, nanostructures have more intense Brownian motion at higher temperatures, which can significantly enhance the effective thermal conductivity. But at high volume fractions, nanoparticles have high potential to be agglomerated at high temperatures.

162 Two-dimensional Materials - Synthesis, Characterization and Potential Applications

A key challenge with nanofluids is that nanoparticles tend to agglomerate due to molecular interactions, such as Van der Waals forces [99, 114]. Agglomeration of nanoparticles increases as filler fraction increases, due to closer particles and higher Van der Waals attraction. Similarly, this issue generates other problems such as viscosity increments (**Figure 4**). Ag‐ glomeration causes the effective surface area to volume ratio to decrease, which impacts the thermal conductivity performance of the fluid. Timofeeva et al. [99, 107] studied the thermal conductivity and viscosity of Al2O3 nanoparticles dispersed in water and EG. It is observed that the main parameters for controlling nanofluids' thermal conductivity enhancement are the geometry, agglomeration state, and surface resistance of nanoparticles. Karthikeyan et al. [109] identified that CuO nanoparticles and cluster size have a significant influence on thermal conductivity of water and EG. Similarly, it is found that nanoparticle agglomeration is time dependent; as time elapsed, agglomeration increased, which decreased the thermal conduc‐ tivity. Wang et al. [115] performed studies on diverse fluids (water, pump fluid, engine oil, and EG) with the addition of Al2O3 and CuO with 28 and 23 nm in diameter, respectively. Viscosity of these systems increase as nanoparticles agglomerate, also thermal conductivity performance is observed to decrease, most probably an effect of the agglomeration of the nanoparticles. Moreover, particle agglomeration is exacerbated by the size of the reinforced fillers. Nasiri et al. observed a reduction in thermal conductivity with time for water-based CNT nanofluids due to agglomeration [114]. However, some reports show that aggregation in water-based Al2O3 nanofluids significantly increases the thermal conductivity of the fluid [116, 117]. In other studies, stable nanofluids showed no significant variation in thermal conduc‐ tivity with time. Yu et al. observed that the thermal conductivity of EG-based ZnO nanofluids [118] and kerosene-based Fe3O4 nanofluids [119] were independent of time. Additionally, engine coolant-based Al2O3 nanofluid exhibited minimum change of thermal conductivity with time [120]. Yu et al. [121] conducted studies on EG-based graphene oxide nanosheets (GON). An enhancement in thermal conductivity at 5.0 vol.% of ∼61% was observed. Thermal conductivity performance was invariable for ∼7 days, reflecting high stability of GON/EG

Because the reinforced particles are so small, weight is less, and the sedimentation probability is less too (**Figure 5**). This reduced nanostructures sedimentation can overcome one of the major drawbacks of suspensions, the settling of particles, and make the nanofluids more stable. In some cases, to enhance the stability of the nanofluids, surfactants or additives are used; nevertheless, there are certain drawbacks of using them.

**Figure 5.** Nanoparticles sedimentation; CuO-reinforced nanofluids over time.

### *3.1.6. Surfactants/additives*

Surfactants are mainly used to stabilize the nanofillers within the conventional fluids, even though these surfactants can affect the nanofluids performance, since surfactants introduce defects at the molecular interfaces [54]. The use of surfactants and dispersion agents has shown to be effective providing repulsion between nanoparticles and reducing agglomeration [49, 81, 122, 123]. Additives are also incorporated to materials to enhance their mechanical properties. For instance, Chen et al. [124] found that the addition of stearic acid (SA) coated MWNTs, and performed as lubricant, improving the friction reduction and anti-wear properties of MWNTs. Non-ionic surfactants were found to strongly interact with graphite surfaces in case of CNTs stabilization within aqueous suspensions [125]. Wang et al. [126] investigated oil with addition of graphite nanoparticles (∼10–30 nm), and also using a dispersant (CH-5) up to 12.0 wt.%. Graphite nanofluids at various filler fractions, from 0.5 to 4.0 wt.%, showed an increase in thermal conductivity from 0.5 to 20%, respectively. These increments were improved with the addition of dispersant (1.5–12.0 wt.%) from 2.4 to 36%. According to Wang et al., this behavior is due to the improvement in dispersibility of graphite with the aid of the dispersant. Oleic acid (OA)-modified TiO2 nanostructures increased the maximum non-seizure load 6–10 times when added to water [127]. Recently, OA was added to h-BN/mineral oil nanofluids [49] showing a decrease of 8 and 3% COF and wear scar diameter (WSD), respectively, compared to the surfactant-less material. Similarly, the addition of OA surfactant in nanolubricants of CuO and MoS2 in palm oil facilitated the reduction of agglomerates, thus improving the tribological properties [123]. In other cases, nanoparticles are used as additives to enhance their useful life, as well as antimicrobial agents. In metal-mechanic industry, for instance, diverse fluids are used to cut or lubricate stamping or metal-cutting processes. Nevertheless, some of them provide a breeding ground for large numbers of microorganisms (fungi/bacteria) which is hazardous to the machine operators [128, 129]. Kumar et al. used silver (Ag) nanoparticles dispersed in paints based on vegetable oil [130], since silver is highly antimicrobial by virtue of its antiseptic properties against several kinds of bacteria, fungi, and viruses [130, 131].

#### *3.1.7. Viscosity*

Viscosity is described as the internal resistance of a fluid to flow. Viscosities in nanofluids are dependent on both fillers geometry and surface properties of nanofillers. As mentioned by Timofeeva et al. [107], elongated particles and agglomerates result in higher viscosity at the same filler fraction due to structural limitation of rotational and transitional Brownian motions. Nguyen et al. [132] have investigated on particle size effect for Al2O3 aqueous-based nanofluids and observed that the particle size effects on viscosity are more significant for high particles concentration. Taha-Tijerina et al. [15] investigated mineral oil reinforced with 2D nanostruc‐ tures of h-BN and graphene at very low filler fractions. It was observed that the viscosity of the nanofluids decreases significantly with temperature (from 16 mm2 /s at room temperature to 2.2 mm2 /s at 100°C), as expected; while the enhancement in viscosity with the addition of 2D-nanofillers is very small (<2% at 313 K). This is an additional advantage of the low filler fractions since the increase in viscosity will decrease the effective thermal conductivity values as well as flow characteristics of the fluid. Moreover, the relatively small increase in viscosity (<30%) at 0.35 wt.% of h-BN is an evidence that the solution is not flocculating [133, 134]. Small deviations from the theoretical values of viscosity at higher concentrations of h-BN/MO may be as a result of a transition from a dilute to a semi-dilute phase or due to the onset of some small aggregation between the h-BN nanosheets [15].

#### *3.1.8. Brownian motion*

Researchers have found that Brownian motion, which is the random movement of particles (**Figure 6**), is one of the key heat transfer mechanisms in nanofluids [62, 115, 135–140]. Keblinski et al. stated possible micro-mechanisms for nanofluids thermal conductivity increase, among which Brownian motion was the reason for this [45]. Moreover, Jang et al. proposed that particles' Brownian motion can induce nanoscale convection, which enhances the thermal conductivity of nanofluids [135]. Brownian motion only exists when the particles in the fluid are extremely small, and as the size of the particles gets larger, Brownian motion effects diminish [61].

**Figure 6.** Representative scheme of Brownian (random) motion of nanoparticles.

#### *3.1.9. Temperature dependence*

stabilization within aqueous suspensions [125]. Wang et al. [126] investigated oil with addition of graphite nanoparticles (∼10–30 nm), and also using a dispersant (CH-5) up to 12.0 wt.%. Graphite nanofluids at various filler fractions, from 0.5 to 4.0 wt.%, showed an increase in thermal conductivity from 0.5 to 20%, respectively. These increments were improved with the addition of dispersant (1.5–12.0 wt.%) from 2.4 to 36%. According to Wang et al., this behavior is due to the improvement in dispersibility of graphite with the aid of the dispersant. Oleic acid (OA)-modified TiO2 nanostructures increased the maximum non-seizure load 6–10 times when added to water [127]. Recently, OA was added to h-BN/mineral oil nanofluids [49] showing a decrease of 8 and 3% COF and wear scar diameter (WSD), respectively, compared to the surfactant-less material. Similarly, the addition of OA surfactant in nanolubricants of CuO and MoS2 in palm oil facilitated the reduction of agglomerates, thus improving the tribological properties [123]. In other cases, nanoparticles are used as additives to enhance their useful life, as well as antimicrobial agents. In metal-mechanic industry, for instance, diverse fluids are used to cut or lubricate stamping or metal-cutting processes. Nevertheless, some of them provide a breeding ground for large numbers of microorganisms (fungi/bacteria) which is hazardous to the machine operators [128, 129]. Kumar et al. used silver (Ag) nanoparticles dispersed in paints based on vegetable oil [130], since silver is highly antimicrobial by virtue of its antiseptic properties against several kinds of bacteria, fungi, and viruses [130, 131].

164 Two-dimensional Materials - Synthesis, Characterization and Potential Applications

Viscosity is described as the internal resistance of a fluid to flow. Viscosities in nanofluids are dependent on both fillers geometry and surface properties of nanofillers. As mentioned by Timofeeva et al. [107], elongated particles and agglomerates result in higher viscosity at the same filler fraction due to structural limitation of rotational and transitional Brownian motions. Nguyen et al. [132] have investigated on particle size effect for Al2O3 aqueous-based nanofluids and observed that the particle size effects on viscosity are more significant for high particles concentration. Taha-Tijerina et al. [15] investigated mineral oil reinforced with 2D nanostruc‐ tures of h-BN and graphene at very low filler fractions. It was observed that the viscosity of

/s at 100°C), as expected; while the enhancement in viscosity with the addition of

2D-nanofillers is very small (<2% at 313 K). This is an additional advantage of the low filler fractions since the increase in viscosity will decrease the effective thermal conductivity values as well as flow characteristics of the fluid. Moreover, the relatively small increase in viscosity (<30%) at 0.35 wt.% of h-BN is an evidence that the solution is not flocculating [133, 134]. Small deviations from the theoretical values of viscosity at higher concentrations of h-BN/MO may be as a result of a transition from a dilute to a semi-dilute phase or due to the onset of some

Researchers have found that Brownian motion, which is the random movement of particles (**Figure 6**), is one of the key heat transfer mechanisms in nanofluids [62, 115, 135–140]. Keblinski et al. stated possible micro-mechanisms for nanofluids thermal conductivity increase, among

/s at room temperature

the nanofluids decreases significantly with temperature (from 16 mm2

small aggregation between the h-BN nanosheets [15].

*3.1.7. Viscosity*

to 2.2 mm2

*3.1.8. Brownian motion*

Nanofluids' effective thermal conductivity and Brownian motion increase with temperature [11, 61–65, 141–143]. Das et al. [62], similarly to Lee et al. [144], observed that Al2O3 and CuO nanofluids thermal conductivity has temperature-dependent influence (in the range from 20 to 50°C); they posed motion of reinforced fillers as an important factor for that. Hu et al. showed a 20% increase in the thermal conductivity of ethanol with the addition of 4.0 vol.% of AlN at 273 K, and a strong temperature dependence of the thermal conductivity [145]. Similarly, Yu et al. [146] research on Al-N nanofluid showed an enhancement of ∼40% with a little effect on temperature from 10 to 60°C. Wang et al. [40] measured thermal conductivity of TiO2 (26 nm) and SiO2 (23 nm) nanoparticles suspended in DiW, EG, and ethanol. The experiment was conducted with 1.0–4.0 vol.% filler fractions at temperatures ranging from 18 to 65°C. Results indicated that thermal conductivity of nanofluids was higher than the base fluids and increased with rise of temperature and filler fraction. For instance, from measurements taken at 18–65°C, TiO2/DiW nanofluid thermal conductivity improved from 3, 4, and 10% to 9, 10, and ∼20% at filler fractions of 1.0, 2.0, and 4.0 vol.%, respectively. As seen from research conducted by Wen et al. [66], the effective thermal conductivity increases with increasing temperature, showing a non-linear dependence after temperatures above ∼30°C. On the other hand, studies by Das et al. [147] on Al2O3/water nanofluids have shown that the thermal-conductivity ratio increased with temperature in a linear fashion.

Jyothirmayee et al. [141] observed a temperature dependence on graphene nanosheets (GnS) reinforced EG and DiW, on temperatures ranging from 25 to 50°C. It was observed that the thermal conductivity increases with increasing graphene concentration and temperature. The thermal conductivity of the base fluids did not show much enhancement as the temperature increases, similar tendency as reported by Jha et al. [148]. An enhancement in thermal conductivity of ∼2.4% is observed at 25°C with a very low filler fraction of 0.008 vol.% of the graphene/EG nanofluid, meanwhile, at 50°C, this increases to ∼17%. At 0.14 vol.%, the enhancement in thermal conductivity is 6.5% and 36% at 25 and 50°C, respectively. The behavior is similar as reported by Chon et al. [64] and Xie et al. [149]. For the 0.14 vol.% graphene/DiW nanofluid, the enhancement is about 13.6% and 94.3% at 25 and 50°C, respec‐ tively. These high increments in thermal conductivity exhibited by the graphene-based nanofluids can be ascribed to the high aspect ratio of defect-free graphene sheets. Walvekar et al. [150] and Ding et al. [151] performed diverse studies on CNTs-water nanofluids, showing that thermal conductivity is highly dependent on temperature as well.

## *3.1.10. Interfacial layering on the liquid-nanostructure interface*

Interfaces are ideal templates for assembling nanoparticles into 2D structures by the nature of the interfaces. At the interfaces, the nanoparticles are mobile and defects of the structures can be eliminated [152]. This ordered structure could have higher thermal conductivity than that of the conventional, therefore an enhancement of the effective thermal conductivity. However, some issues could be addressed when a surfactant or dispersant is used [66]. Interfacial layering refers to a phenomenon at the liquid–particle interface where liquid molecules are more ordered than those in the conventional liquid; therefore the interface effect could enhance the thermal conductivity by the layering of the liquid at the solid interface (giving that crystalline solids possess much better thermal transport that liquids) [45, 153], by which the atomic structure of the liquid layer is significantly more ordered than that of the conventional liquid. Various researchers have suggested that there is a liquid layering on the nanoparticles, which helps enhance the heat transfer properties of the nanofluid [151, 154–156]. Yu et al. [156] proved the formation of layers by the liquid molecules close to a solid surface, even though the thickness and thermal conductivity of the nanolayers are not well known yet. Ren et al. [157] found, through a theoretical model, that adding liquid layering on the nanoparticles an increase in layer thickness leads to higher thermal conductivity increment; as larger the size of the suspended particles, the weaker appear the effects of the nanolayer and the thermal motion.
