Chapter 2 LITERATURE REVIEW. 2.1 Review on Making Of Nanofluids. Several studies, including the earliest investigations of

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1 Chapter 2 LITERATURE REVIEW 2.1 Review on Making O Nanoluids Several studies, including the earliest investigations o nanoluids, used a two-step method in which nanoparticles or nanotubes are irst produced as a dry powder and then dispersed into a luid in a second processing step. In contrast, the one-step method entails the synthesis o nanoparticles directly in the heat transer luid. The two-step and one-step methods are discussed in more detail in sections and respectively Two Step Process The preparation o nanoluids begins by direct mixing o the base luid with the nanomaterials. In the irst step, nanomaterials are synthesized and obtained as powders, which are then introduced to the base luid in a second step. Nanoparticles can be produced rom several processes [11,12 ] which can be categorized into one o ive general synthetic methods. These ive methods are: (i) transition metal salt reduction [13,14], (ii) thermal decomposition and photochemical methods [15], (iii) ligand reduction and displacement rom organometallics [16] (iv) metal vapor synthesis, and (v) electrochemical synthesis [17]. Transition-metal nanoclusters are only kinetically stable because the ormation o the bulk metal is its thermodynamic minimum. Thereore, nanoclusters 20

2 that are reely dissolved in solution must be stabilized in a way that prevents the nanoclusters rom coalescing, because such agglomeration would eventually lead to the ormation o the thermodynamically avored bulk metal [18]. Bonnemann et al [16] developed a method or the production o very small (< 2 nm) and stable nanoparticles via chemical reduction pathways, which might be suitable or application in nanoluid synthesis. Organoaluminum compounds have been used or the reductive stabilization o mono and bi-metallic nanoparticles. Triorganoaluminum compounds were employed as both the reducing agent and colloid stabilizer, which lead to the ormation o an organo-metallic colloidal protecting shell around the particles [19,20 ]. This modiication o the Alorganic protecting shell leaves the particle size stable. Silver nanoparticles are one o the most widely studied nanomaterials because they exhibit unusual optical, electronic and chemical properties, which depend on their size and shape [21,22,23]. Silver is also one o the most thermally conductive metals and its use in cooling applications would be interesting. Besides silver nanoparticles, Xuan et al. [24] have used commercially obtained Cu nanoparticles to prepare nanoluids in both water and transormer oil by sonication in the presence o stabilizers. Similarly, Kim et al. [25] prepared nanoluids consisting o commercially obtained CuO nanoparticles in ethylene glycol by sonication without stabilizers. The optimum 21

3 duration o sonication was ound to be 9 hours and the average nanoparticle size was 60 nm. The two-step process is commonly used or the synthesis o carbon nanotube based nanoluids. Single-wall carbon nanotubes (SWCNTs) and Multi-walled carbon nanotubes (MWCNTs) are cylindrical allotropes o carbon. SWCNTs consist o a single cylinder o graphene, while MWCNTs contain multiple graphene cylinders nesting within each other [26]. The carbon nanotubes are usually produced by a pyrolysis method and then suspended in a base luid with or without the use o a suractant. Some authors suggested that the two-step process works well only or nanoluids containing oxide nanoparticles dispersed in de-ionized water as opposed to those containing heavier metallic nanoparticles [27,28,29]. Since nanopowders can be obtained commercially in large quantities, some economic advantage exists in using two-step synthesis methods that rely on the use o such powders One step process Few methods exist or the preparation o nanoluids through a one step process. These methods include the thermal decomposition o an organometallic precursor in the presence o a stabilizer [30], chemical reduction [31], and polyol synthesis [32, 33]. 22

4 The polyol method is one o the most well known pathways to noble metal nanoparticles [34, 35, 36]. In the polyol process, a metal precursor is dissolved in a liquid polyol (usually ethylene glycol), ater which the experimental conditions are adjusted to achieve the reduction o the metallic precursor by the polyol, ollowed by atomic metal nucleation and metal particle growth [37]. The direct-evaporation technique was developed by Choi et al [28]. It consists o a cylinder containing a luid which is rotated. In the middle o the cylinder, a source material is vaporized. The vapour condenses once it comes into contact with the cooled liquid (Figure 2.1). The drawbacks o this technique however, are that the use o low vapour pressure liquids are essential and only limited quantities can be produced. Various single-step chemical synthesis techniques can also be employed to produce nanoluids. For example, Brust and coworkers [36] developed a technique or producing metallic nanoparticles in various solvents by the reduction o metal salts to produce colloidal suspensions or a wide range o applications, including studies o thermal transport. Excellent control o size and very narrow size distributions can be obtained by using such methods [2]. A submerged arc nanoparticle synthesis system (SANSS) was developed to prepare CuO nanoparticles dispersed uniormly in a dielectric liquid (deionized water). The method successully 23

5 produced a stable nanoluid [37]. In principle, a pure copper rod is submerged in a dielectric liquid in a vacuum chamber. A suitable electric power source is used to produce an arc between C which melts and vaporizes the metal rod in the region where the arc is generated. At the same time, the deionized water is also vaporized by the arc. The vaporized metal undergoes nucleation, growth and condensation resulting in nanoparticles dispersed in deionized water. Nanoluids containing CuO particles o size 49.1 ± 38.9 nm were obtained [37]. Resistively Heated Crucible Cooling System Liquid Figure 2.1 One-step nanoluid production system (Choi et.al. [28]) 2.2 Review on Thermophysical Properties o Nanoluids The thermal conductivity measurement o nanoluids was the main ocus in the early stages o nanoluid research. Considering the application o heat transer luids, heat transer coeicients o nanoluids in low condition is also very 24

6 important. The important properties other than thermal conductivity that aect the heat transer coeicients are density, heat capacity and viscosity o dispersions (see Fig.2.2 to Fig. 2.5). Since the nanoparticle concentration in nanoluids usually are very low (<1 vol%), the particle eect on the density and heat capacity o the dispersions is not signiicant. However, due to the small particle size, the nanoparticle eect on the viscosity o the dispersions might be remarkable, especially or nanotube or other high or low aspect ratio nanoparticle dispersions. Some o the properties o nanoparticles & base luids are listed in Table 2.1 useul or assessing the nanoluid properties. Table.2.1 Thermophysical properties o Nanoparticle & base luids Property Water Ethylene glycol Cu Al2O3 CuO Ti O2 C ( J/kg K ( kg/m 3 ) k (W/m K) α (m 2 /s) Density The density o a nanoluid can be calculated by using mass balance as ρ n (1)ρ ρ (2.1) p For typical nanoluids with nanoparticles at a value o volume raction less than 1%, a change o less than 5% in the luid density is expected (see Fig.2.2) 25

7 2.4 Speciic Heat The speciic heat o a nanoluid can be calculated by using energy balance as (1- ) C pc p C n (2.2) n Using these equations, one can predict that small decreases in speciic heat will typically result when solid particles are dispersed in liquids. For example, adding 3 vol% Al2O3 to water would be predicted to decrease the speciic heat by approximately 8% compared with that o water alone (see Fig.2.3). The simple equations above may need to be modiied i nanoparticles are ound to exhibit a size dependent speciic heat. 2.5 Viscosity The rheological and aggregation behaviors o spherical nanoparticles in liquid suspensions have been studied quite extensively (Meitz, Yen et al. [38]). They suggested at very low volume raction (the shear viscosity o a hard sphere suspension can be predicted by Einstein ormula n (1 2.5 ) (2.3) This equation was extended by Brinkman [39] as n 1 (1 ) (2.4) 2.5 The experimental results or the viscosity o copper nanoluids rom Xuan s group [24] showed good agreement with this model. 26

8 Batchelor [40] gave another ormula to calculate the viscosity o particle suspensions (<=0.01) n (2.5) However, most o the work was ocused on concentrated nanoparticle dispersions. Das sk et al. [41] conducted experiments on 1~4 vol% Al2O3 nanoparticles (38nm) in water dispersions. They reported nanoluids showed Newtonian behavior and viscosities were higher than water. They also suggested or many o the spherical nanoparticles dispersions, the volume ractions o nanoparticle seems low enough to apply Einstein or Batchelors equations to predict the increase o the viscosity in dispersions. The data reported by Chang et al.[42] in CuO nanoluids also indicted that the viscosity o nanoluids increased with decrease o particle size due to large speciic area and electrostatic orces. Wang et al [43] measured the viscosities o Al2O3 in water nanoparticle dispersions which were created by dierent dispersing methods. An increase between 20% and 30% was reported to 3vol%. They indicated that the particle concentration, size and particle shape, the aggregation structure o 27

9 Figure 2.2 Eect Nanoluids density with volume raction 28

10 Figure 2.3 Eect o Nanoluids speciic heat with volume raction 29

11 Figure 2.4 Eect o Nanoluids Prandtl number with volume raction 30

12 Figure. 2.5 Eect o Nanoluids thermal diusivity with volume raction 31

13 nanoparticles will also aect the rheological behaviors o particle dispersions. They also gave a correlations as ollows or Al2O3 + water & EG and ound to be nearer to experimental data as shown in Fig.2.6. For Al2O3 + water n (2.6) For Al2O3 + Ethylene Glycol n (2.7) However, Pak & Cho [44] reported a three times higher viscosity or Al2O3 (13nm) + water nanoluids that o water. The authors suggested dierent dispersing techniques which can lead to dierent particle or agglomerate size may be the reasons or this large discrepancy. They also gave correlations or For Al2O3 + water n 2 ( ) (2.8) For TiO2 + water n 2 ( ) (2.9) Chen et.al.[45] also gave correlation or the viscosity o TiO2 + Ethylene glycol as ollows For TiO2 + Ethylene glycol 10.6 ) 2 n ( (2.10) 32

14 For Cu + water 2 n ( ) (2.11) Tseng and Li [46] correlation or viscosity o TiO2 + water as ollows n e (2.12) Kulkarni et.al.[ 47] presented the correlation or the viscosity o CuO + water as ollows A ln n A B (2.13) T 2 B In the present work the above equations are used wherever necessary and ound to be nearer to experimental data available in the literature. 2.6 Thermal Conductivity o Nanoluids In this section the measurement o thermal conductivity o the nanoluids is reviewed and important actors are discussed. The possible mechanisms are explained or the high thermal conductivity o nanoluids is presented in the ollowing sections. 33

15 Figure 2.6 Eect o Nanoluids viscosity with volume raction 34

16 2.6.1 Metallic nanoparticle dispersions Choi et.al [48] pioneered the work in the nanoluids by dispersing nanometer sized particles into liquids. They suggested that compared with the suspension o larger particles, nanoparticles can be kept in dispersions or much longer time. Because nanoparticles are so small, they may act like macromolecules in solution, dramatically reducing erosion and clogging and their larger surace areas improve heat transer. Ater that, numerous experimental results have been reported and this concept has been proved. Enhanced thermal conductivities have been reported or metal nanoparticle dispersions by dierent research groups. The metals applied in dispersion are gold, sliver, copper, iron and aluminum. Eastman et.al [49] reported that copper nanoparticles dramatically increased the thermal conductivity o base luid, ethylene glycol (EG). The eective thermal conductivity o nanoluids with 0.3vol% o copper nanoparticle (~10 nm) was 40% higher than that o pure EG when thioglycolic acid was used as dispersing agent. The nanoparticle dispersion without dispersant in it had a much lower increase ratio (~ 5%) compared to an acid containing dispersion with same particle loading (0.3 vol%). They also suggested Aging o the dispersion can decrease the eective thermal conductivity o 35

17 the nanoluids. The authors suggested that particle size is an important actor or the eective thermal conductivity o nanoluids. Another work on copper nanoparticle in EG dispersions was done by Asseal et.al [50]. The nanoparticle applied in their work had a mean diameter o 10 nm, but containing agglomerates with sizes greater than 50 nm. With 0.5 vol% o copper nanoparticles, the eective thermal conductivity o EG increased 3.5%. They suggested result is much lower than the one in Eastman s work which may be caused by the agglomerates in the dispersions. Li and Xuan [51] studied the particle size eect on copper nanoparticle in water dispersions. They ound that the dispersion containing smaller particles (20 nm) had a higher thermal conductivity than that containing bigger particle (100 nm). For example, by adding 2 vol% o 20 nm copper nanoparticles, the eective thermal conductivity o the base luid increased 23% while the increase was around 15% or the case when 100 nm particle were used. They suggested that larger surace area o smaller particles may help or heat transer occurring at the interace. They also measured the thermal conductivity o Al2O3 nanoparticle dispersion and compared it with that o copper nanoluids. They ound the thermal conductivity o 2 vol% Al2O3 nanoluids only had a 6.3% increase compared with water while copper nanoluid showed a 23% increase. It indicated that the thermal property o 36

18 the particle is one o the essential actors or the properties o nanoluids. Naked gold nanoparticle in the 10~20 nm range and monolayer protected gold nanoparticle were prepared and dispersed in water and toluene by Patel et.al [52]. The naked nanoparticle dispersion showed thermal conductivity enhancement o 5%~21% in the temperature range rom 30~60 0 C at very low loading ( vol%) while the dispersion containing nanoparticle with a thiolate covering showed 7% ~ 14% or a loading o vol%. It is surprising that the particle volume raction o particle in this work is one or more order magnitude lower than other cases mentioned above, and the dierences o the thermal conductivities o two nanoluids at dierent temperatures may suggested surace action can have a signiicant eect on the behavior o the nanoluids. They also measured thermal conductivity o sliver nanoparticle in the 60~80 nm range and compared with those o small gold nanoparticle dispersions. It showed that even with higher particle loading, the thermal conductivity o the larger particle dispersion was still comparatively lower than small particle dispersions. This result was consisted with other studies o the particle size eect. Hong et.al [53] studied the thermal conductivity o iron nanoparticle in EG dispersions. The mean diameter o the nanoparticles was 10 nm, however, they existed in the dispersion 37

19 as clusters due to the absent o dispersing agent. The authors observed that the thermal conductivity o Fe nanoluids was increased nonlinearly up to 18% as volume raction o the nanoparticle was increased up to 0.55 vol%. Compared with copper nanoluids reported by Eastman et.al [49], higher increase ratios o thermal conductivities or Fe nanoluids indicated the dispersion o high thermal conductivity materials is not always eective or improving the thermal properties o nanoluids. The authors suggested that the size o nanoparticle clusters or the microstructure in the dispersion is an important actor or improving the thermal conductivity o luids Nonmetallic nanoparticle dispersions Compared with metal nanoparticle dispersions, experimental work started earlier or oxide nanoparticle dispersions. Al2O3 and CuO are most common candidates being applied or nanoluids research. Masuda et.al [27] reported a 30% thermal conductivity increase o water by adding 4.3 vol% o Al2O3 (average diameter ~13 nm) nanoparticles. However, in the research done by Lee et.al [54] the same amount (4.3 vol%) o Al2O3 (average diameter ~ 38 nm) nanoparticles only lead to 10% thermal conductivity increase o water. It is another example to show the importance o particle size on thermal conductivity o nanoluids. In addition to the smaller size o particle, the nanoluids prepared by the Masuda [27] group 38

20 contained chemical dispersant which was supposed to modiy the surace o nanoparticles while there was no such chemical added in Lee s work. This result is consisting with the one observed in Eastman s [49] work on the metallic nanoparticle dispersions. Lee et.al [54] also studied another three systems, Al2O3 in EG, CuO in water, CuO in EG. The Cuo particles they used in their work were smaller than Al2O3 nanoparticles, which had an average diameter o 24 nm. They ound that in low volume raction range (upto 5 vol%), the thermal conductivity increase ratios moved almost linearly with particle loading, but with dierent rates or each system. It indicates thermal conductivity depends on both dispersed particle and base luids. For the systems using the same base luid, kn /k in CuO nanoparticle was always higher than that o Al2O3 nanoluids which may be caused by the smaller size o CuO particles. The thermal conductivity increase ratios o EG nanoluids were always higher than those o water based nanoluids. It suggested that the increase ratio was dependent on the thermal conductivity o the base luids. There is another very interesting study o thermal conductivities o Al2O3 nanoparticle dispersions. Xie et.al [55] used a series o dierent alumina nanoparticles with dierent particle size, speciic area and crystalline phase and dispersion them into distilled water, EG and pump oil. The experimental results showed that adding 39

21 nanoparticles into base luids led to increased thermal conductivities much higher than calculated rom conventional models. The enhanced ratio o thermal conductivity increased with particle loading. They ound that the increase ratio o thermal conductivity decreased with increase o ph value o aqueous dispersions. For the dispersions containing the same nanoparticle, the enhancement ratio o the thermal conductivity was reduced with the thermal conductivity o the base luid. This result was consistent with Lee s results [54]. For the dispersions based on the same base luid, the thermal conductivity increase ratio was dependent on speciic surace area or particle size o the nanoparticles. There was an optimal speciic surace area 25 m 2 g -1 (corresponding particle size 60 nm) which gave highest increase ratio or the thermal conductivity o nanoluids. The particle smaller or larger than 60 nm gave lower thermal conductivities. The authors explained this maximum by two actors: interace area at which heat transer happened, and reduced intrinsic thermal conductivity due to the scattering o phonons at particle-particle boundaries. When the particle size is much larger than mean ree path o phonon (35 nm), the irst actor dominated. The thermal conductivity o the nanoluid increases with decrease o the particle size. When the particle size is close to mean ree path o phonon, the thermal conductivity o nanoluid may decreases with 40

22 decrease o particle size. In another work rom the same group, the thermal conductivity o Al2O3 nanoparticle in water dispersion was reduced adding dispersing agents. This result was contrary to the work done by Eastman et.al [49] on copper nanoluid. Wang et.al [43] dispersed Al2O3 and CuO nanoparticles into our base luids: distilled water, engine oil, EG and pump oil. They suggested or both nanoparticles, the thermal conductivities o water based nanoluids were always lower than those o EG based nanoluids which proved the results rom other groups. However, compared to Al2O3 nanoparticle dispersions, EG and engine oil based nanoluids gave the higher increase ratios o thermal conductivity than water and pump oil based nanoluids. It indicated that when same particles were dispersed into base luid, thermal conductivity o the base luid was not the only actor to aect the increase ratio o thermal conductivity o nanoluid. The temperature eect o thermal conductivity enhancement in nanoluids has been presented by SK Das et.al [41].They studied thermal properties o Al2O3 and CuO nanoparticles at dierent temperatures. The particle sizes in their work were 38.4 nm or Al2O3 nanoparticle and 29 nm or CuO nanoparticles. Their measurement results conirmed that the level o thermal conductivity increase at room temperature as observed by Lee et.al [54]. A dramatically increase o thermal conductivity ratios has 41

23 been observed at high temperatures. A two or our old increase in thermal conductivity enhancement was reported over a small temperature range 20 ~50 0 C. They suggested this makes nanoluids more attractive as cooling luids which were likely to work at higher temperature than room temperature. Li and Perterson [56] conducted an experimental investigation to examine the eects o variations in the temperature and volume raction on the eective thermal conductivity o CuO and Al2O3 water suspensions. Results demonstrated that nanoparticle material, diameter, volume raction and bulk temperature have signiicant eects on the thermal conductivity o the nanoluids. They observed three times enhancement in Al2O3/water suspension, increase in mean temperature rom 27 to 34.7 o C. They presented correlations or Al2O3/ water and CuO/ water nanoluids k k n n k k k k (T ) 0.462( Al2O3 + water) (2.14) (T ) 0.307(CuO + water) (2.15) Thermal conductivity o SiC nanoparticle dispersions have been studied by Xie et.al [57], 26 nm spherical SiC particle and 600 nm cylindrical particles were dispersed in distilled water and EG. They ound the thermal conductivities o nanoluids are higher than corresponding base luids and increase ratio o thermal conductivity increased linearly with particle volume raction. 42

24 Surprisingly, the increase ratio or 26 nm particles in water dispersions was lower than that o 600nm particle dispersions. The thermal conductivity increase ratio or same particle dispersions seemed independent o base luids. Beck, M.P et al.[58] conducted experiments on alumina nanoparticles dispersed in ethylene glycol in temperature range o K to K. They also compared theoretically by taking shape actor o n=3.4 in Hamilton and Crosser model and ound to be in good agreement with experimental results. Kim et al.[59] conducted experiments on water and ethylene glycol based nanoluids containing Al2O3, ZnO,TiO2 nanoparticles and ound variation with volume raction and size dependence. They also observed the eect o particle size change by laser ablation or ZnO nanoluids and reported thermal conductivity is inversely proportional to the particle size and dependence appears to be linear. Hong et al.[60] proposed TiO2, Al2O3, WO3 nanoparticles dispersed in water and ethylene glycol and ound large enhancement than baseluids. They reported surace to volume ratio o nanoparticle is a primary actor in determining the thermal conductivity o nanoluids. Murshed et al. [61] conducted both experimental and theoretical study on thermal conductivity and viscosity o nanoluids. They 43

25 reported both thermal conductivity and viscosity o nanoluids increase with volume raction and also ound strong dependent on temperature. They proposed two static mechanisms based models to predict thermal conductivity o nanoluids having spherical and cylindrical nanoparticles considering particle size, interacial layer and volume raction showed reasonably good agreement with experimental data Carbon nanotube dispersions The large intrinsic thermal conductivity o carbon based nanostructures combined with their low densities compared with metals, makes them attractive or use in nanoluids. Moreover, high aspect ratio particle are more eective than low aspect ratio ones and much more attractive than spherical particles [62]. All o the reasons above lead to extensive studies on carbon nanotube dispersions to improve heat transport recently. The irst article on thermal conductivity o nanoluids containing carbon nanotubes was published by Choi et.al [62]. Multiwalled carbon nanotubes were dispersed into oil with loading up to 1 vol% nanotubes. The thermal conductivity o nanoluids containing nanotubes (MWNTs) was measured at room temperature and results were compared to the predictions calculated rom several theoretical models. Nanotubes lead to an anomalously large increase in the thermal conductivity o base luid (up to a 160% 44

26 increase with 1 vol% nanotubes), which is by ar the highest thermal conductivity enhancement ever achieved in a liquid. They suggested the nature o heat conduction in nanotubes dispersion and an organized structure at the solid-liquid interace might be responsible or the high thermal conductivity o nanotubes dispersion. Moreover, the thermal conductivities o all spherical nanoparticle dispersions showed linear dependence on the solid loading in the range investigated (1-5 vol%), while thermal conductivities o MWNT nanoluids showed nonlinear increase with nanotubes volume ractions at low solid loadings (<1 vol%). Choi et al [62] suggested it may be caused by the existence o interaction among nanotubes even at low volume ractions. However, carbon nanotubes have hydrophobic surace and can not be dispersed into most o common heat transer luids like distill water and EG without surace treatment and/or existence o dispersants. A concentrated nitric acid treatment was applied by Xie at.al [63] to disentangle MWNT aggregates and produce uniorm nanotubes dispersions. The acid treatment introduced oxygen containing unctional groups onto nanotube suraces, so they could be dispersed into polar liquids like distilled water and EG without additional dispersants or suractants and into non-polar liquids like decene with oleylamine as suractant. All the nanotube dispersions showed substantial increase o thermal conductivity 45

27 and the thermal conductivity enhancement were much higher than those calculated rom conventional models. For 1 vol% particle raction, the thermal conductivity enhancements are 19.6%, 12.7% and 7% or decene, EG and water. This trend was consistent with the one showed in alumina dispersions (Lee,choi et.al [54]) that thermal conductivity enhancement decreased with increase o thermal conductivity o base luids. However, thermal conductivity increase in this work were just moderate by compared with the results in Choi s[62] work which reported 160% increase or 1 vol% particles. Moreover, the thermal conductivity enhancements seemed to increase linearly with particle loading at low volume raction (upto 1 vol%) while Choi [62] et.al reported a nonlinear change. The authors suggested those discrepancies would be attributed to dierent base luids and preparation methods o nanoluids. Assael et.al [50] dispersed carbon MWNTs into water with the help o the suractant, sodium dodecyl sulate (SDS).The maximum thermal conductivity enhancement or 0.6 vol% nanotubes dispersion was 38% compared with pure water. Another attempt to disperse carbon nanotube into water has been done by Wen et.al [64]. Instead o SDS they used sodium dodecylbenzene sulonate (SDBS) as dispersant in their work. Eects o particle concentration and temperature on the thermal conductivity o 46

28 nanoluids were studied. Their results showed that the thermal conductivity o nanoluids increased with increase o particle loading, however, the dependence was nonlinear. The enhancement ratio increased almost linearly when particle raction was lower than 0.2 vol% but the dependence tended to level o above that loading. The increase ratio o 0.46 vol% nanoluid was around 22% at room temperature which was much lower than that o nanotube in oil dispersion (50%) with the same particle loading reported by Choi et.al [62] but much higher than that o nanotube in water dispersion (4%) made by Xie et.al [63]. The authors suggested the possible reason may be the dierent thermal conductivities o carbon nanotubes and dierent thermal resistances at the interace. Thermal conductivity ratios in carbon MWNT dispersion increased with temperature linearly on 20~30 0 C range but the dependence leveled o when temperature was higher than 30 0 C. This tendency was quite dierent rom that in Al2O3 or CuO nanoparticles dispersions which showed a linear increase with temperature in 20~50 0 C range. Dispersant ailure happened in MWNT in water dispersions when temperature was higher than 60 0 C and nanoluids became unstable. The dispersions o carbon nanotube in EG have been prepared by Cho et.al [65]. Three dierent methods to make the nanoluids were applied: 1) Sonication 2) Sonication plus dispersant 47

29 (ployacrylamide-co-acrylic acid) and 3) Sonication plus acid treatment. The thermal conductivity ratios were 16%, 14% and 15% or those three cases respectively at same particle volume raction (1 vol%). The thermal conductivity ratios or sonication nanoluids were 16%, 19% and 23% or 1,2,3 vol% nanoluids which showed a nonlinear tendency similar to the one reported by Wen et.al [64] in aqueous dispersions. An enhancement ratio o 12.4% or nanotube in EG dispersion without the help o dispersant has been reported by Liu et.al [66]. This result is quite close to the results o Choi s [62] work. They also measured the thermal conductivity o nanotube in engine oil dispersions with N-hydrosuccinimide as dispersant. An increase ratio o 30% has been claimed or 2 vol% dispersion system which was much lower than the result reported by Choi et.al [62]. Biercuk et al. [67] measured the eective thermal conductivity o suspensions o single wall carbon nanotubes (SWNT s) and vapor grown carbon ibers (VGCF) in epoxy using a comparative method. Results showed 125% and 45% improvements or 1 vol% SWNT s and VGCF, respectively. They ound choi et al. [62] on thermal properties o SWNT s epoxy composites showed similar improvement o the thermal conductivity. They pointed out that the bonding o nanotubes could be an important actor or thermal transport characteristics. 48

30 Jana et al [68] conducted experiments on nanoluids containing SWNT, Cu, Au, separately and hybrids o them in water. Enhancement in thermal conductivity o CNT, Cu, Au was observed whereas hybrid CNT-Au and CNT-Cu did not improve the thermal conductivity. They also reported Cu nanoluids showed best results o 74% increase with base luids and nonlinear enhancement in CNT nanoluids. However, both Cu and CNT nanoluids showed drastic decrease o their thermal conductivity with time due to sedimentation and agglomeration Based on the above exhaustive review a thermal conductivity o nanoluids, the inerences drawn and the experimental enhancement ound by dierent researchers is presented in Appendix I. It is observed rom the table that most o the experimental work is carried out or water and Ethylene glycol as baseluids with either Al2O3 or CuO as nanoparticles. The appendix I can be used as an immediate reerence or inding out enhancement o thermal conductivity or dierent nanoluids at dierent concentrations and dierent particle sizes. The observations recorded by earlier researchers in inding enhancement are also presented or ready reerence. The next section is denoted to review the work carried out by several researchers in the past to ind out the thermal conductivity o nanoluids theoretically. 49

31 2.7 Models or Thermal Conductivity o Nanoluids The thermal conductivity enhancement o nanoluids was higher than those predicted rom conventional models (in Table 2.2) or larger size particle dispersions as in Fig.2.7. Thereore, dierent researchers (Li and Xuan [83]). Keblinski et.al [84]; Xie etal [85]) explored the mechanisms o heat transer in nanoluids, and proposed our possible reasons or the contribution o the system: 1. Brownian motion o the particle 2. Molecular-level layering o the liquid at the liquid/solid interace 3. The nature o the heat transport in nanoparticles 4. The eects o nanoparticles clustering Figure 2.7 Comparison o the Conventional Models with the Experimental Data [41]. 50

32 Table 2.2 Convectional models or eective thermal Models Maxwell (1873) [76] Hamilton & Crosser [77] Bruggerman [78] Jerey [79] Davis conductivity o solid-liquid suspensions. k k k k k n n n k k n Expression 3( 1) 1 ( 2) ( 1) k p ( n 1) k k p ( n 1) k ( n 1) ( k ( k k k 3 1k 3 11k p kp 3 11 k k pk (3...) 4 p ) p ) ( 2) 16(2 3) 1 Where ; = Kp/K 2 kn 3( 1) 1 ( ) k ( 2) ( 1) 2 [80] Lu & Lin [81] Where ()=2.5 or = 10, and ()=0.5 or = kn ; Where ; = Kp/K k 2 3 Landau k n 1/3 1/3 1/3 k Lishitz/Looyenga p k k k [82] For better investigation o these mechanisms some o the authors have even used computational methods. In the ollowing sections each possible mechanism will be discussed and theoretical work on thermal conductivity o nanoluids will be reviewed Brownian motion o the particles In 1827, Robert Brown[86] examined the orm o Clarkia pulchella pollen particles immersed in water and observed that many o these particles were in continual motion that arose rom neither currents in the luid, nor rom its gradual evaporation, but rather 51

33 that appeared to belong to the particles themselves. This constant and irregular motion increased as the size o the particle decreased and continued or the entire time that the particle remained in suspension. Further observation o this Brownian motion illustrated the irregular energy and momentum exchanges o molecules caused by the collision between particles and molecules, and indicated a strong, temperature dependence. Jang and Choi [87] derived a theoretical model that involves our modes are shown in Fig. 2.8 such as Figure 2.8 Modes o Energy transport in Nanoluids (Jang and Choi [87]) 1. Collision between base luid molecules(k (1 )), 2. Thermal diusion in nanoparticles in luids(kp ), 3. Collision between nanoparticles due to Brownian motion(neglected), 4. Thermal interaction o dynamic or dancing nanoparticles with the base luid molecules ( h δ T). 52

34 Where h ~ kb / dpre 2 Pr 2 and δ ~3dp presents the heat transer coeicient or the low past nanoparticles and the thickness o the thermal boundary layer, respectively. The advantage o the model is to include the eects o concentration, temperature, and particle size. The resulting expression or the eective thermal conductivity o nanoluids is d k (2.16) 1 p 1 p d p. k k 3C k Re Pr n in which subscript and p represents base luid and nanoparticles. D is diameter o particle or molecule. C1 is proportional constant and Pr is Prandtl number o nanoluids. Rep is deined as Cd p Re p (2.17) v in which C and v are the random motion velocity o nanoparticles and dynamic viscosity o the base luid. This model has been compared with experimental results rom several research groups (Masuda, Ebata et al.[27]; Lee, Choi et al.[28]; Eastman, Choi et al.[29] ; Das, Putra et al. [41]). Most o the data ell onto the predicted curves calculated rom model and it seems this model not only includes the particle volume raction and temperature eect on the thermal conductivity o nanoluids, but also predicts the strong size dependent conductivity. I the hypothesis in this 53

35 paper is correct, the increased thermal conductivity enhancement with decrease o the nanoparticles size which happened in most reports can be related to Brownian motion o the nanoparticles. Kumar et al. [88] pointed out that since heat transer is a surace phenomenon, higher surace area to volume ratio o nanoparticles can explain the enhancement o thermal conductivity o nanoluids. A stationary model has been developed based on this theory, showing that the enhancement in eective thermal conductivity increased with the reciprocal o nanoparticles diameter. Moreover, they developed a moving particle model based on Brownian motion o the nanoparticles at dierent temperatures was combined with stationary model to indicate temperate eect on the thermal conductivity o nanoluids. Chon et.al [89] developed an empirical correlation or the thermal conductivity o Al2O3 nanoluids with dierent particle size (11nm ~ 150nm) and temperature (21 ~ 71 0 C) based on Brownian motion o the nanoparticles. Bhattacharya et.al [90] developed a technique to compute the thermal conductivity o nanoluids using Brownian dynamics simulation in which they omitted the motion o liquid molecules and their eects on nanoparticles and represented them as random orce and riction terms. In this simulation, the Langevin equation o motion was used to describe the particle movement 54

36 and the eect o solvent molecules and was represented by a combination o random orces and rictional terms. The potential energy between the two particles was described by an exponential model as: r ij d ij A exp B (2.18) d Where d is the particle diameter, A and B are the parameters or the system, and is the distance between particles j and i. Their simulation based on interparticle potential predicted the eective thermal conductivity o nanoluids to a good level o accuracy in comparison with some experimental data (Eastman, Choi et.al [28]; Wang et.al [43]). Koo et.al [91] compared the relative eects o nanoparticle motion mechanisms on the eective thermal conductivity o dilute nanoparticle dispersions. They ound the eect o Brownian motion was more signiicant by actor o 10 6 and 10 8 than those o thermophoresis and osmophoresis. Ater reviewing the models mentioned above and perorming an order o magnitude analysis, Prasher et al [92] draw a conclusion that local convention caused by Brownian motion o the nanoparticle was the mechanism which can be used to explain thermal conductivity enhancement o nanoluids. Based on a traditional model (Nan, et al.[93]) or k o solid liquid composite 55

37 which considers interace resistance, they developed a semiempirical model to predict thermal conductivity o nanoluids. By itting the experimental data or aqueous Al2O3 and CuO nanoparticle dispersions ( Masuda, Ebata et al.[27]; Lee, Choi et al.[28] ; Xie, wang et al. [43]; Das, Putra et al. [41]) with various dp, and T. They ound most o data can be it by this model, when A= and m= % can be applied or water based nanoluids. Prasher et al.[94] in their recent experimental investigation, a drop o dye in pure water diuses much more slowly than the same drop o dye in Al2O3/Water nanoluids. It was also determined that the optimal volume raction or the diusion is around 0.5%. These results would appear to provide signiicant evidence o the eect o the Brownian motion on the enhanced thermal conductivity o nanoluids. Thereore, Brownian motion seems to be one o the possible mechanisms to be applied or predicting thermal conductivity enhancement in nanoparticle dispersions, especially in spherical nanoparticle dispersions. Most o the important actors aecting the enhancement o thermal conductivity in nanoluids can be included in models base on this mechanism, such as particle size, temperature, thermal conductivity o particle and base luid and viscosity o base luid. 56

38 2.7.2 Interacial layering o liquid molecules Some literature (Nan, Birringer et al.[95]) addressed the eect o interacial resistance (Kapitza resistance) on thermal conductivity o particulate composites due to weak interacial contact. They set up a theoretical model to predict thermal conductivity o composites by including interacial resistance. According to this model, the eective thermal conductivity should decrease with decrease o the nanoparticle size which is contrary to most o the experiment results or nanoluids. Yu et al [96] reported that molecules o normal liquids close to a solid surace can organize into layered solid like structure. This kind o structure at interace is a governing actor in heat conduction rom solid surace to liquid. Choi et al [28] pointed out that this mechanism contributed to anomalous thermal conductivity enhancement in nanotube dispersions. However, Keblinski et al [84] indicated that the thickness o the interacial solid-like layer is too small to dramatically increase o the thermal conductivity o nanoluids because a typical interacial width is only on the order o a atomic distance (1nm). So this mechanism only can be applied to very small nanoparticles (<10nm). In order to ind the connection between nanolayer at interace and the thermal conductivity o nanoluids, Yu et al. (Yu, Richter et al. [96]; Yu and Choi [97]) modiied the Maxwell equation or spherical 57

39 particles and Hamilton-Crosser equation or non-spherical particles to predict the thermal conductivity o nanoluid by including the eect o this ordered nanolayer. They applied this model to it some experimental data in which smallest nanoparticles were dispersed (Lee, Choi et al[28]; Eastman, Choi et al [29] ) and ound the model predicted the experimental data well. However, the model ailed to predict the results or Cu nanoluids with suractant. The simulation work done by Xue et al[98] indicated that the strength o the bonding between liquid and solid is very important in determining interacial thermal resistance. Nanoluids with weak atomic bonding at interace exhibit high thermal resistance and wetting systems have small interacial thermal resistance. Adding dispersant into dispersion systems or surace treatment will certainly change the atomic bonding at interace and lead to varied interacial resistance. Xue [99,100] developed a novel model which was based on Maxwell theory and average polarization theory or eective thermal conductivity o nanoluids by including interace eect between solid particle and base liquid. He considered solid nanoparticle and interacial shell (nanolayer o liquid molecules) as a complex nanoparticle and set up the model based on this concept. The theoretical results obtained orm this model were in good 58

40 agreement with the experimental data or alumina nanoparticle dispersions (Xue, Wu et al. [101] )and showed nonlinear volume raction dependence or thermal conductivity enhancement in nanotube dispersions (Choi, Zhang et al. [62]). Xie et al. (Ren, Xie et al.[102]; Xie, Fujii et al.[103]) investigated the eect o interacial layer on the eective thermal conductivity o nanoluids. A model has been derived rom general solution o heat conduction equation and the equivalent hard sphere luid model representing microstructure o particle suspensions. Their simulation work showed that the thermal conductivity o nanoluids increased with decrease o the particle size and increase o nanolayer thickness. The calculating values were in agreement with some experimental data (Masuda, Ebata et al.[27];lee, Choi et al. [28]; Eastman, Choi et al. [29]). Recently, a new thermal conductivity model or nanoluids was developed by Yu et al.[104]. This model was based on the assumption that monosized spherical nanoparticle are uniormly dispersed in the liquid and are located at the vertexes o a simple cubic lattice, with each particle surrounded by an organized liquid layer. A nonlinear dependence o thermal conductivity on particle concentration was showed by this model and the relationship changed rom convex upward to concave upward. A comparison o theoretical prediction and experimental data showed that 59

41 calculation value were much higher than experimental results which indicate that there is a potential to improve the eective thermal conductivity o nanoluids. Generally, the solid like nanolayer at liquid-solid interace can not be used to explain most o experimental data in which nanoparticles larger than 10nm were dispersed. However, interacial thermal resistance which had been noticed in particle dispersion, both composites and larger particle in liquid suspensions, will be a critical actor to aect the thermal conductivity o nanoluids because o the huge interace area or those nanosized particles. Inclusion o dispersant or surace treatment o nanoparticles will dramatically aect the thermal conductivity o nanoluids by changing the interactions between solid and liquid surace Nature o heat transer in nanoparticles Keblinski (Keblinski, Phillpot et al. [84) estimated the mean ree path o a phonon in Al2O3 crystal is ~35nm. Phonons can diuse in the 10nm particles but have to move ballistically. In order to make the ballistic phonons initiated in one nanoparticle to persist in the liquid and reach another nanoparticle, high packing ractions, soot-like particle assemblies, and Brownian motion o the particles will be necessary to keep the separation among nanoparticles to be small enough. 60

42 However, Xie et al. (Xie, Wang et al. [55]) ound in their research about alumina nanoluids that when the particle size close to the mean ree paths o phonons, the thermal conductivity o nanoluid may decrease with particle size because the intrinsic thermal conductivity o nanoparticle was reduced by the scattering o phonon at particle boundary. However, this result was not in agreement with most o the experimental results rom other groups. Choi et al.[28] indicated that sudden transition rom ballistic heat conduction in nanotubes to diusion heat conduction in liquid would severely limit the contribution o ballistic heat conduction to overall thermal conductivity o nanotube dispersions. They suggested that both ballistic heat conduction and layering o liquid molecules at interace contributed to the high thermal conductivity o nanotube dispersions. The nature o heat transer in nanoparticles or the ast ballistic heat conduction can not be the mechanism works alone to explain thermal conductivity enhancement o nanoluids due to the barrier caused by slow heat diusion in liquid. Other mechanisms need to be combined with it to ully understand the enhancement o the thermal conductivity in nanoluids Nanoparticle clusters Local nanoparticle clustering is another possible mechanism oered by Keblinski, Phillpot et al [84]. They suggested that the 61

43 eective volume o a cluster can be much larger than the volume o the particles which will lead to higher overall thermal conductivity o nanoluids. Clusters with very low packing actor which is deined as ratio o the volume o the solid particles in the cluster to the total volume o cluster, and very larger eective volume might be one o the reasons or the unexpected thermal conductivity enhancement o nanoluids. However, the author also pointed out that the clusters existing in the dispersion may cause the settlement o particles or creating particle-ree regions with high thermal resistance. Except or local clusters, the nanoparticles with aspect ratio much higher or lower than one can reach the percolation threshold at very low loading. Eq.2.19 shows an empirical ormula (Garboczi, Snyder et al.[105]) developed to predict the percolation threshold, Pc as unction o the particle aspect ratio, A. p c A A (2.19) A 12.33A 1.763A 1.658A The calculation results rom this equation were plotted in Fig 2.9. When the particles reach the percolation threshold, they can build up three dimensional network structures in the nanoluids and change the properties o the base luids substantially. 62

44 Figure 2.9 Percolation threshold or particles with dierent aspect ratios (Garboczi, Snyder et al.[ [105]) A theoretical model which included Brownian motion and diusion limited aggregation was developed by Xuan et al.[83]. The calculation values o enhancement o thermal conductivity o nanoluids containing 10nm copper nanoparticles agreed with their experimental data (Li and Xuan[51]). However, according to this model, the thermal conductivities enhancement o nanoluids should decrease with cluster size. Wang et al.[106] developed another theoretical model to predict the thermal conductivity o nanoluids with cluster in it. The speciic size eect on thermal conductivity and liquid monolayer adsorbed on to solid surace were also included in the model. 63

45 Recently, Gao et.al [107] presented dierential eective medium theory by taking into account both physical and geometrical anisotropy o the nanoluids to predict the enhanced thermal conductivity o nanoluids. Interestingly, their simulation results showed a nonlinear dependence o thermal conductivity enhancement on volume raction o nanoparticles which agreed with the experimental results rom Choi et al [28]. Based on the above review on theoretical thermal conductivity models o nanoluids a summary o dierent models and equations by dierent researchers is presented in Appendix II. 2.8 Convection heat transer properties o Nanoluids Increasing the heat transer coeicient o the heat transer luids is very important or Nanoluids applications. Compared with the experimental work on thermal conductivity o Nanoluids, there were ewer papers that discuss the heat transer coeicients o Nanoluids in convective lows. Choi [108] pointed out that heat transer coeicient should increase with low rates or with the thermal conductivities o the luid, while other properties o the nanoluid system, such as heat capacity, density and viscosity are kept same as the base luid. I a nanoluid can have high thermal conductivity at low volume ractions, a high heat transer coeicient might be obtained without increasing the pumping power. In heat exchanger design, the length o the exchanger 64