# Investigating On Thermal Conductivity And Viscosity Biology Essay

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Augmentation of heat transfer of CNT nanofluids especially for SWCNT and MWCNT has been investigated extensively among researchers. Most of the CNT nanofluids were prepared using a two-step method with the consideration of thermal conductivity and viscosity as their thermo physical properties. In this paper the different characteristic of thermal conductivity and viscosity of CNT nanofluid including nanofluid preparation methods, temperature, particles sizes and shape, types of surfactant and volume fraction effects are thoroughly compiled and reviewed. The ineffectual thermal conductivity is influenced by the Brownian motion while the enhancement ratio of thermal conductivity is mostly influenced by the increasing in temperature and nanotube loading. The existing experimental results about the increasing of viscosity for CNT are augmented according with an increase of volume concentration and decrease with temperature enhancement. However there are some contradictory results on the effect of parameters to the thermal conductivity and viscosity. The effective viscosity and thermal conductivity are shown in the theoretical and experimental result. The existing models for predicting thermal conductivity of CNT nanofluid, including HamiltonCrosser model, YuChoi model and Xue model were verified while the existing model for viscosity nanofluids consist of Brickman model, Krieger and Dougherty model were shown. Hence, the objective of this study is to investigate the effect of several parameters that bring the influence to the thermal conductivity and viscosity on CNT nanfluids.

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Keyword: Carbon Nanotube, Nanofluids, Thermal Conductivity, Viscosity

## Introduction

Nowadays, considerable attention has been given to nanofluids technology because of high demand and its various applications in the industry. Due to its small size and have high in specific area of nanoparticles which is exist and less than 100nm in a liquid, this nanopartical will allow for more heat transfer when the tiny size produce micro convection fluids to give highest impact in the heat transfer performance. The properties of nanofluids include high thermal conductivity, small amount of clogging during flow passages, lack of scoring on pipe wall, and can improve the heat transfer for long term stability of the system (Choi 1995; M. Chandrasekar 2005). Nanofluids can be beneficial in a way that the system can be miniaturized in order to reduce the inventory of heat transfer fluid while also resulting in cost saving. Moreover nanofluids will reduce the pumping power as compared to pure liquid to achieve equivalent heat transfer intensification. Hence, nanofluids can be explained as a solid liquid mixture consists of nanoparticles and based liquid that has a lot of potential to improve the efficiency in thermal conductivity and viscosity. Nanoparticles (Al2O3, Graphite, TiO2, CuO, CNT, Cu, TNT, and etc) and based liquid (Water, EG, DW, Distilled Water, Terpineol, PG, Ethanol) are dispersed together for enhancing thermo physical properties of nanofluids.

In a study, one of the rarely used particles types in nanofluids during an investigation is carbon nanotube (CNT). Although in small fraction, CNT is the most greatest particles to increase the thermal conductivity (S.U.S. Choi 2001; M.J. Biercuk 2002). Due to its very high thermal conductivity and very large aspect ratio (S. Berber 2000; P. Kim 2001; M. Fujii 2005), many researcher are showing more interest in using CNT in their experimental and theoretical study. The type of CNT that commonly being studies are Single Walled Carbon Nanotube (SWCNT), Few Walled Carbon Nanotube (FWCNT), Pristine Carbon Nanotube (PCNT), Double Walled Carbon Nanotube (DWCNT) and Multi Walled Carbon Nanotube (MWCNT). Hwang et al. (Y. Hwang 2007) reported that SWCNT present the highest one in thermal conductivity compare than DWCNT and MWCNT.

Table 1 and table 2 show the summary of literatures about the viscosity and thermal conductivity of CNT nanofluids for different types of parameters. Some of the latest review paper Nasiri et al. (A. Nasiri 2012) discussed the effect of CNT structure to the thermal conductivity and stability only without considering other aspects. Aladag et al. (Bahadir Aladag 2012) studies and focus on the effect of nanoparticles at low temperature to the viscosity only. Moreover Mahbubul et al. (I.M. Mahbubul 2012) show the latest investigation on the viscosity of various nanofluids with emphasizing on the CNT nanofluids and the thermal conductivity. Therefore, complete studies considering all aspects seem to be required in this field. Hence the purpose of this article is to provide the available information about the temperature, particle sizes, volume concentration, pH value, and ultrasonication time effect over thermal conductivity, viscosity, density and specific heat for CNT nanofluids.

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Table 1

Summary of literatures about the viscosity of CNT nanofluids for different type of parameter

Year

Reference

Based Fluids

Particles names

Related to

## T

## Ps

## Ut

## V%

## pH

## S

2008

(L. Chen 2008)

DW,EG and Gly

CNT

## âˆš

## âˆš

2008

(Lifei Chen 2008)

Distilled Water

MWCNT

## âˆš

## âˆš

2008

(H. Chen 2008)

DW

TNT

## âˆš

## âˆš

2009

(H. Chen 2009)

EG

TNT

## âˆš

## âˆš

2009

(H. Chen 2009)

EG, Water

TNT and TiO2

## âˆš

2010

(A. Amrollahi 2010)

Water

FWCNT and MWCNT

## âˆš

## âˆš

2011

(Tran X. Phuoc 2011)

Water

MWCNT

## âˆš

2011

(Kalpana Tumuluri 2011)

DW

MWCNT

## âˆš

## âˆš

2012

(Bruno Lamas 2012)

DW + EG

MWCNT

## âˆš

2012

(Zhaoguo Menga 2012)

EG

MWCNT

## âˆš

2012

(M. Fakoor Pakdaman 2012)

Heat Transfer Oil

MWCNT

## âˆš

2012

(Bahadir Aladag 2012)

Water

CNT and Al2O3

## âˆš

Note: Gly, PAO, and W refer to glycerol, polyalphaolefin, and water respectively. And, T, Ps, Ut, V%, pH, S, and Vf means temperature, particles size, ultrasonication times, vol.% effect, pH value, surfactant and volume fraction.

Table 2

Summary of literatures about the thermal conductivity of CNT nanofluids for different type of parameter

Year

Reference

Based Fluids

Particles names

Related to

## T

## Ps

## Ut

## V%

## pH

## S

2007

(Y. Hwang 2007)

DW + Mineral Oil

MWCNT, Fullerene and CuO

## âˆš

## âˆš

2008

(H. Chen 2008)

Water

TNT

## âˆš

## âˆš

2009

(Weiting Jiang 2009)

Water

CNT

## âˆš

## âˆš

2010

(Vijay S. Raykar 2010)

DW

CNT

## âˆš

## âˆš

2010

(Majid Emami Meibodi 2010)

Water

SWCNT and MWCNT

## âˆš

## âˆš

## âˆš

## âˆš

## âˆš

## âˆš

2010

(A. Amrollahi 2010)

Water

FWCNT and MWCNT

## âˆš

## âˆš

2011

(Kalpana Tumuluri 2011)

DW

MWCNT

## âˆš

## âˆš

## âˆš

2011

(Zeinab Talaei 2011)

Distilled Water

FWCNT and MWCNT

## âˆš

## âˆš

## âˆš

## âˆš

## âˆš

2011

(Aida Nasiri 2011)

Water

SWCNT, DWCNT, FWCNT, MWCNT

## âˆš

## âˆš

## âˆš

2012

(A. Nasiri 2012)

DW

SWCNT, DWCNT, FWCNT, MWCNT

## âˆš

## âˆš

## âˆš

2012

(Jacobi 2012)

Water

MWCNT

## âˆš

## âˆš

2012

(Sivasankaran Harish 2012)

EG

SWCNT

## âˆš

2012

(C.A. Nieto de Castro 2012)

Water

SWCNT and MWCNT

## âˆš

## âˆš

2012

(Zhaoguo Menga 2012)

EG

MWCNT

## âˆš

## âˆš

## âˆš

2012

(M. Fakoor Pakdaman 2012)

Heat Transfer Oil

MWCNT

## âˆš

Note: Gly, and PAO, refer to glycerol, polyalphaolefin, respectively. And, T, Ps, Ut, V%, pH, S, and Vf means temperature, particles size, ultrasonication

times, vol.% effect, pH value, surfactant and volume fraction.

Table 3:

The selective summary of the characteristics the types of SWCNT and MWCNT

Type CNT

Findings

SingleÂWalled Carbon Nanotube (SWCNT)

It was the 2nd observation made by IIjima

The basic structure only has single layer of grapheme structure (several nanometers diameters and several micrometer lengths)

Most of the grapheme structure aligned and pack together to develop a typical ropes of 10-100 parallel tubes

SWCNT will develop the Field Effect Transistor (FETs) because of their important in the electric properties

Advantage in thermal conductivity incerament and disadvantages when high cost as well as very difficult to de-agglomeration

MultiÂWalled Carbon Nanotube (MWCNT)

It was the 1st observation made by IIjima

The basic structure has a multiple layer of grapheme structures (up to 10-100 of concentric tubes of graphite sheet with adjacent shell separation of 0.34nm)

On each tube the carbon atoms are arranged in a helical fashion along the tube axis. The outer diameter 10nm and length of 10-100Î¼m

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Examples of our workMechanical and thermal transport properties MWCNT which make them suitable for application to structural composites, energy storages and heat transfer.

MWCNT have highest degree of purity, long-distance crystalline order, and their ability to be dispersed in water, allowing to obtained stable suspensions, are particularly good applicant to evaluate the properties of nanotube based nanofluids. But for it disadvantages are low cost and easy de-agglomeration

Table 4

Summary of literatures about the types of surfactant of CNT nanofluids in the previous study

Author

Type of CNT

Type of Surfactant

## CG

## SDBS

## SDS

## NIPAAm

## PVA

## SOCT

## HCTB

## NaDBS

## PVP

(Hong H 2007)

SWCNT

## âˆš

(Brian Wright 2007)

SWCNT

## âˆš

(Jesse Wensel 2008)

SWCNT

## âˆš

(Y. Hwang 2007)

MWCNT

## âˆš

(Lifei Chen 2008)

MWCNT

## âˆš

(Milanova 2009)

SWCNT

## âˆš

(Lifei Chen 2010)

MWCNT

## âˆš

(Mark Horton 2010)

SWCNT

## âˆš

(Vijay S. Raykar 2010)

CNT

## âˆš

## âˆš

## âˆš

(Majid Emami Meibodi 2010)

SWCNT

## âˆš

MWCNT

(Kalpana Tumuluri 2011)

MWCNT

(Laura Fedele 2011)

SWCNT

## âˆš

(Aida Nasiri 2011)

SWCNT,DWCNT,

MWCNT,FWCNT

## âˆš

(Jacobi 2012)

MWCNT

Note: Types of surfactant are Cationic Gemini (CG), NÂisopropylacrylamide (NIPAAm), Polyvinyl Alcohol (PVA), Sodium Dodecylbenzenesulfonate (SDBS), Sodium Dodecylsulfate (SDS), Salt and Oleic Acid, Cetyltrimethylammoniumbromide (CTAB), Dodecyl Trimethylammoniumbromide (DTAB), Sodium Octanoate (SOCT), Hexadecyltrimethylammoniumbromide (HCTAB), Polyvinylpyrrolidone (PVP) and Gum Arabic (GA).

## Carbon Nanotube and Cylindrical Particles

2.1 Carbon Nanotube

CNT was defined as a unique inner hollow tubular structure of nanometer diameter rolled with graphite plates with large length/diameter ratios and without any aperture in the tube wall. The carbon network of the shells is closely related to the honeycomb arrangement of the carbon atoms in the graphite sheets (VN 2004; Hou PX 2008). CNT was reported exist as armchair, zigzag, and chiral types. Only armchair nanotubes are truly metallic, while the others present as a semiconductor. CNT are hydrophobic in nature and thus cannot be dispersed in water under normal condition. It's exposing to have a chance to entangle and form cluster or agglomerates if it's still being dispersed. The aqueous suspension of different functionalization CNT structure was homogenized for a month (A. Nasiri 2012). Moreover, the specific characteristics of CNT are high specific area, porous nature, low density, high strength as well as unique structure, and good electrical conductivity.

Some researchers have much attention to concern that CNT perform as a high thermal conductivity as a great potential for significant heat transfer enhancement in their superior properties compare to other metallic or non-metallic nanofluids. Hence by apply large amount of CNT will produce by either arc discharge or thermal decomposition of hydrocarbon vapour. Compare to the result from Su et al. (Fengmin Su 2011) in the investigation to ammonia based CNT nanofluid binary are lower than those of the water based CNT nanofluids and show a different trends. Form their statement it has been proven the thermal conductivity of water based CNT nanofluids is higher compare to the ammonia based CNT nanofluids. Hence the well organize nanotubes are particularly good candidates to evaluate the properties of nanotube-based nanofluids. Table 3 show the properties and behaviour for the selective of CNT type.

2.2 Cylindrical Particle

There are several and few works has been done and numerically investigated so far for cylindrical nanoparticles shape as well as a more complete analytical solution that considers the effect of nanolayes structure. Some theoretical model are explaining the effective thermal conductivity of nanofluids containing spherical nanoparticle and most of them used Choi (Choi 1995) theory, that consider nanolayer separated from cylindrical nanoparticle shapes. In addition a nanofluid consisting of base fluid and complex nanoparticles is statistically homogeneous and isotropic. The decrease of nanotube diameter, the thermal conductivity increases if the thickness of nanolayers increases (Sadollah Ebrahimi 2007; Sadollah Ebrahimi 2010; Zeinab Talaei 2011). When the diameter of nanotubes are less than 30 nm, the enhancement of thermal conductivity becomes very significant, if we increase the nanolayers thickness. Hence from the figure1, it will express the cylindrical nanoparticles base fluid and modes of energy transport in nanofluids.

Fig.1 The Cylindrical nanoparticle in base fluid and modes of energy transport in nanofluids, where d present as nanolayer thickness, rpnanoparticle radius and l is length of nanotubes.

## Application of CNT and Cylindrical Particles based nanofluids

Nanofluid has become an important fluid in number of industrial sector including power generation, chemical production, air-conditioning, energy supply, transportation and microelectronics. Most of the application of nanofluids always contributes in thermal system field and for the refrigerant system. Heat transfer nanofluids were first reported by Choi (Choi 1995) of the Argonne National Laboratory, USA in 1995.

Until now there are still did not have any review paper will concern about the application of CNT only. CNT are beneficial in solar absorption application where the solar energy get to become a renewable energy to reduce the environmental impact. Moreover, containing MWCNT under load range of 200N-800N under reasonable concentration will emphasizes the friction and wears because the advance lubricant can save the energy and can improve the productivity through reliability of engineering system. No wonder MWCNT composite was evaluated as lubricant additive due to its ability in friction reduction and good extreme pressure. CNT also become a tool in nanodrug delivery system where it beneficial to improve the efficiency of drug action. It can be functionalized together with bioactive peptides, proteins, and also nucleic acids as well as deliver the cargos to cells and organ (Xie 2011). For example when a researcher published on their literature review about "formulation of a SWCNT-dexorubicin complex with extremely high drug loading efficiency". Hence CNT nanofluids have displayed significantly exciting forthcoming applications and good performance in commercialization market. Further discussion and review need to be consider for CNT nanofluid after this.

## Preparation of CNT and Cylindrical Particles of nanofluids.

A two-step method for synthesizing nanofluids is the most suitable method for preparing stable, homogeneous and surfactants free rather that one-step method for measuring viscosity and thermal conductivity. Due to the nanofluids properties, this method work well for oxide CNT nanoparticles because of its simple preparing method. Basically, there are two type method two disperse CNT in the based fluids (water or EG) namely mechanical method and chemical method (Hilding 2003; GARG May 2008). For mechanical method includes ultrasonication method which disperse nanotube particle by a series of bubbles nucleation and collapse events that can separate the nanotube easily but if it not done in control way, it will decrease the corresponding of aspect ratio where is physically damage the nanotube. Ultrasonic disruptor, ultrasonic bath or ultrasonic probe commonly being use as the basic equipment to the disperse CNT and during the preparation there have three physical mechanism need to be consider in CNT which are cavitations of the fluids, localize heating, and formation of free radicals. By this physical mechanism, it will reduce the length of CNT and reduce the tendency to entangle which help them disperse easily in the base fluids. The chemical method includes surfactant and CNT functionalization by using acid as it chemical properties. Surfactant or activator adding is one of the general methods to prevent sedimentation happened during dispersion. Adding surfactant together with CNT can improve the stability of nanoparticles aqueous suspension as well as increase in nanoparticles sizes. But at a high temperature, the bonding between surfactant and nanoparticle can be damaged. Hence by using this method it can change the wetting and adhesion behaviour which help reducing their tendency to agglomerate. There are a few of instrument for stability inspection. The list include UVÂVisspectrophotometer, Zeta Potential Test, Sediment Photograph Capturing, TEM (Transmission Electron Microscopy) and SEM (Scanning Electron Microscope), Light Scattering, Three Omega and Sedimentation Balance Method (A. Ghadimi 2011). All of these instruments already have their own test specification such as to quantitatively colloidal stability of the dispersion, to validate the quality of the nanofluids, and to find the sedimentation amount.

## Influence of Surfactant to the Thermal Conductivity and Viscosity

Choosing the right surfactant is the most important thing during the process. It could be anionic, cationic, or nonionic. Some example of surfactant types are Cationic Gemini (CG), Sodium Dodecylbenzenesulfonate (SDBS), Sodium Dodecylsulfate (SDS), Salt and Oleic Acid,Cetyltrimethylammoniumbromide (CTAB), Dodecyl Trimethylammoniumbromide (DTAB), Sodium Octanoate (SOCT), Hexadecyltrimethylammoniumbromide (HCTAB), Polyvinylpyrrolidone (PVP) and Gum Arabic (GA). Cationic Gemini surfactant was using as a stabilizer in the study by Chen et al. (Lifei Chen 2010) to prepare the stable MWCNT based water nanofluids. Stabilizing MWCNT and improving thermal conductivity are happened when reducing the spacer chain lengths of Gemini surfactant. It is different types of surfactant was study by Phuoc et al. (Tran X. Phuoc 2011) where even though adding a small amount of chitosan, it will stabilized MWCNT in water and increase the value of thermal conductivity. However there are some disadvantages when adding the surfactant at high temperature especially above 60Â°C, where it will damage the bonding between particles of nanofluids. It can be concluded that the longer ultrasonication time and higher value in temperature cannot give the better performance in thermal conductivity (Majid Emami Meibodi 2010). Table 4 present the summary of literatures about the types of surfactant of CNT nanofluids. From this table, SDBS and Gum Arabic are the most common types of surfactant to be used in a research. Table 5 show the stability of CNT when added together with surfactant.

Table 5

The stability of nanofluid on thermal conductivity and viscosity

Researcher

Surfactant +CNT

Thermal Conductivity

Viscosity

Phuoc et al. (Tran X. Phuoc 2011)

0.2 wt.% Chitosan + 2wt.% CNT

0.621 (W/m.K)

0.354 (Pa.s)

0.2 wt.% Chitosan + 3wt. % CNT

0.656 (W/m.K)

0.641(Pa.s)

Meibodi et al. (Majid Emami Meibodi 2010)

0.11wt% Gum Arabic + 0.2 wt.% SWCNT

1.12 (W/m.K)

## -

Chen et al. (Lifei Chen 2010)

0.6wt% Cationic Gemini + 0.1wt% MWCNT

18.2%

## -

## Thermal Conductivity Characteristic of Carbon Nanotube Nanofluids

It was observed the enhancement in liquid thermal conductivity is the most important factor that can be investigated to prove the heat transfer enhancement. Recent literatures show that the thermal conductivity is the most widely studied in the publisher. The nanofluids especially CNT have the features of adjustable thermal conductivity and long term stability. Figure 2 illustrated the combination effect on the efficient in thermal conductivity. According to Wen et al.(D. Wen 2009) from the graph, if aggregated particles in the fluids bring about particle chains or clusters, the predicted thermal conductivity would be significantly higher and might be of a strong function of the aggregates dimension and the radius gyration of the aggregates.

C:\Users\fadhillah\Pictures\Capture3.PNG

Fig.2 Aggregation effect on the effective thermal conductivity (D. Wen 2009)

6.1. Theoretical Study

Several theoretical models have also been attempted to develop a predictive tool for thermal conductivity enhancement but due to the complex structure of nanofluids, there are several correlation of model are ineffectively to accurate the value of thermal conductivity. The theory has been carried out to understand the flow of heat transfer mechanism and to develop models for accuracy predicting thermal conductivity of nanofluids. However some researcher have been reported studies of the thermal conductivity theory, have a limited to spherical shape nanoparticles rather than containing cylindrical nanofluids but it is not widely accepted. Murshed et al. have develop a model for the prediction of thermal conductivity of nanofluids (Î»effÂnf) containing cylindrical nanoparticles. Table 6 demonstrated the most popular convectional models of thermal conductivity of solid/liquid suspensions in the previous study.

Table 6

Conventional models of thermal conductivity of solid/liquid suspensions

Researcher

Expression or Models

Maxwell (Maxwell 1881)

Hamilton and Crosser(R.L. Hamilton 1962)

(R.L. Hamilton 1962)

Jeffery (D.J. Jeffery 1973)

Meibodi et al.

(Majid Emami Meibodi 2010)

0.7982 0.1021xA + 0.0517xB-0.0308xC-0.0107xD+ 0.0468xE-0.0219xF - 0.0279xG-0.1119xH

Hwang et al.(Y. Hwang 2007)

Hemanth et al.

(Hemanth K D 2004)

Mursyed et al.

(S.M.S. Murshed 2005)

Xue (Xue 2005)

Yu and Choi

(W. Yu 2003)

Murugasan et al.(C. Murugesan 2010)

Chon et al.(C.H. Chon 2005)

Chibante et al.(Chibante 2005)

Note: Where shape factor n = 3 for spherical particles and n = 6 for cylinder particle, ðœ™p is the particle volume fraction and Î»f and Î»p are the thermal conductivities of the base fluid and particles, x denotes the coded variable. In the case of noncategorical factors, if a variable with low level Kl and high level Kh takes the value of K, its coded variable can be calculated as where Kave=(Kh+Kl)/2. In the case of stability evaluation, the order of being significant for different effects is as follows: H (time) > C surfactant type) > B (nanoparticle weight percent) > A (nanoparticle size) > D (surfactant weight percent) while r1 and rs denoting the liquid and solid particle radii and É› present as volume fraction of nanoparticles and (1-É›) present as the volume fraction of the liquids. K= thermal conductivity of the binary system; A quantifies the particle shape; k1 = thermal conductivity of the base fluid; k2 = thermal conductivity of carbon nanotubes; = volume loading of carbon nanotubes.

6.2. Experiment Study

Based on Paul et al. (G. Paul 2010) the paper concentrate in techniques to compute the thermal conductivity of nanofluids include transient hot wire technique, thermal constants analyzer technique, KD2 Pro thermal properties analyzer Phuoc et al. (Tran X. Phuoc 2011), steady state parallel plate method, cylindrical cell method, temperature oscillation technique and 3& omega method. The thermal conductivity of CNT suspension in most previously study reported experiments was measure by transient hotÂwire method. Through this study the temperature will increase by using hot wire which related to the thermal conductivity of fluids flow. There are a few of factor or parameter influencing the extraordinary enhancement of heat transfer will need to be consider to measure thermal conductivity which are list as effect on temperature, effect on the weight percentage, effect on volume fraction, effect on ultrasonication time, effect on pH value and effect on the particle size. Among all types of CNT based water nanofluids or EG or DI Water , SWCNT suspension showed the best result in the cast of stability as well as thermal conductivity enhancement greater than the based fluids and improvement in the both specification decrease for structure with additional walls. Moreover, the diversity between the thermal behaviours of these structures decreases as the CNT wall increase (A. Nasiri 2012). Table 7 present the thermal conductivity measurement procedure and stability inspection mechanism for CNT nanofluids while table 8 show the percentage enhancement of thermal conductivity according to different type of CNT and cylindrical particles at the different particle sizes.

6.2.1. Effect of Temperature

Nasiri et al. (A. Nasiri 2012) discuss the effect of temperature to thermal conductivity where it enhancement of nanofluids containing 0.25wt% of each CNT structure is not only increase with increase in temperature. From this study the factor that leads to have higher value in thermal conductivity is when the enhancement result of temperature is prepared in many uniform dispersion and suspension of nanoparticle in the nanofluids. Moreover, the variation of normalized thermal conductivity for SWCNT is higher than the other structures. The investigation to the effect of temperature on thermal conductivity was prepared at room temperature with respect to time by using SWCNT, DWCNT, FWCNT and MWCNT. The thermal conductivity will increase with linear relation between these types of temperature at range between (15- 40oC). Same result in the experimental data indicate that thermal conductivity of CNT based water nanofluids will increase with increase in temperature (A.J. Schmidt and McKinley 2008). On the other hand, at the different temperature and different type of CNT and based fluids, the thermal conductivity data of MWCNT based water nanofluid reported by Tumuluri et al. (Kalpana Tumuluri 2011) was observed that MWCNTs yielded the highest thermal conductivity enhancement in the range between (28-32 Â°C). However, it is notified that the dependence levels off when temperature is out of this range.

The thermal conductivities by water compare to EG are increase by Harish et al. (Sivasankaran Harish 2012) studied. The thermal conductivity enhancement ratios of CNT nanofluids also at different temperatures using CNT based EG were present by Chen et al. (Lifei Chen 2008). It is observed that the thermal conductivities of CNT nanofluids are higher than those of the base fluids at all the tested temperatures. However, CNT nanofluids show different thermal conductivity enhancement behaviours. It is seen when all the nanofluids at different volume fractions of 0.01, 0.006, and 0.002, the thermal conductivity enhancement ratios almost keep constant when the tested temperatures vary. According to Ding et al. (Yulong Ding 2006), CNT based water nanofluid was adding together with 0.25wt.% of gum Arabic and the effective thermal conductivity increase with increase in temperature above 30oC However, the effective thermal conductivity levels off at 20-25oC with concentration above 0.5wt.%.

The temperature also influences the thermal conductivity of CNT based glycol nanofluids (Zhaoguo Menga 2012). The enhancements in thermal conductivity are higher as compared to glycol at room temperature because the heat conduction through CNT is much faster than through glycol. The CNT dispersed in glycol provide a fast heat-conducting network thus significantly enhancing the overall thermal conduction. The conclusion can be made that thermal conductivity of CNT based glycol nanofluids will increase with temperature. However, from the continued experiment, the thermal conductivity of CNT based glycol nanofluids is not inconsistent and unpredictable because the influences from the many factors include the morphology, structure and agglomeration tendencies.

Moreover due to the Ramaprabu et al. (Ramaprabhu 2009) the temperature dependence of the thermal conductivity by investigate about Au-MWCNT, Ag-MWCNT, and Pd-MWCNT nanofluids is studied at different concentrations. It has been found that thermal conductivity increases in temperature where indicating that the Brownian motion of the nanoparticles suspended in the nanofluid plays a major role in the heat transfer. For temperatures between the range (15-40Â°C), a nearly linear dependence of thermal conductivity enhancement on temperature was obtained. It was observe the thermal conductivity enhancement CNT based water nanofluid for SWCNT, DWCNT and MWCNT are 15.6%, 14.2% and 12.1% at temperature 55oC and at volume fraction 0.002 vol.% (Lifei Chen 2010).

6.2.2. Effect of Weight Percentage/Concentration

The magnitude of effective thermal conductivity enhancement for MWCNT based EG reported in this work is in consistent with the existing literature data, however at several different in nanotube concentrations. This difference could be endorsed to the aspect ratio of the material used, purity level, and treatment process adopted to set up the nanofluid dispersion. The measured thermal conductivities from Castro et al. (C.A. Nieto de Castro 2012) demonstrate the enhancement of effective thermal conductivity of two ionanofluids and one nanofluid as a function of concentration of MWCNT at room temperature. It is seen that the effective thermal conductivity of these ionanofluids (lINF) increase significantly (almost linear) with increasing in weight concentration of MWCNT.

Ding et al. (Yulong Ding 2006) reported concentration at 0.5wt% with temperature 30oC increase the effective thermal conductivity. The thermal conductivities by using SWCNT based EG increased with increase SWCNT loading where the maximum enhancement is 14.8% at a loading of 0.21 vol.% (Sivasankaran Harish 2012).

6.2.3. Effect of pH

Knowing that the stability of aqueous solution nanofluids directly links to its electro kinetic properties by due to its high surface charge density and strong repulsive forces which can stabilize a well disperse suspension. There have been limit studied have been publish about the liquid acidity on the thermal conductivity increment, but they have some a few researcher have taken a concern on it. Xie et al. (H. Xie 2003) explained that by simple acid treatment a CNT suspension gained a good stability in water. It is continues by Meibodi et al. (Majid Emami Meibodi 2010) it seems that suitable surfactant and optimum value of pH and surfactant concentration depend on nanoparticle and base fluid characteristics. Hence by according to their results, pH values have minor effect on the thermal conductivity of CNT nanofluids.

It is different from Talaei et al. (Zeinab Talaei 2011) where they use the several method to conduct the experiment where are the first, second and third method consist of 6.8mmol/g, 5.2mmol/g and 2.4mmol/g of carboxylic group concentration. The thermal conductivity of MWCNT based water nanofluids is enhanced by three methods in the event that carboxylic concentration of the first method is more than second and third methods. There is concern that the highest thermal conductivity is diminished by defects (e.g., a vacancy defect, an isotope impurity, or a StoneWales defect) generated during the CNT synthesis, or by functionalize process. Hence they analyzed that the influence of defects on the heat transport in the low-dimensional structure of CNTs could be high, much larger than in bulk materials.

The second researcher use the same investigating using the carboxylic group concentration (Z.Talaei 2010). In this work, Distilled water and MWCNT were used to produce nanofluids. Among them, two methods were chosen for functionalized MWCNT consist the first method, functional groups on nanotubes are commonly made by treating them in strong oxidants such as sulfuric acid (H2S04) and nitric acid (HN03).For the second method, consist of 40 mg pristine SWCNT and 50 ml deionised water were added to a flask and dispersed with the aid of an ultrasonic water bath around 60 min at room temperature. It can be concluding that the thermal conductivity of MWCNT based water nanofluids are enhanced by second method in the event that Carboxylic concentration of the first method is more than second method.

6.2.4. Effect of Volume Fraction

According to the Hwang et al. (Y. Hwang 2007) shows the thermal conductivity enhancements of water based MWCNT and fullerene nanofluids as a function of the particle volume fraction. The results show that the thermal conductivities of water based MWCNT nanofluids increase with increasing particle volume fraction, while the thermal conductivities of water based fullerene nanofluids are decreased with increasing particle volume fraction. It is believe that the thermal conductivity of fullerene is 0.4W/mK which is lower than that of water. It is follow when study the thermal conductivity enhancements of oil based MWCNT and fullerene nanofluids as function of the particle volume fraction. The thermal conductivity of MWCNT nanofluid is much higher than that of fullerene nanofluid because the thermal conductivity of MWCNT is much higher than that of fullerene. It is also believed that the thermal conductivity of nanoparticles strongly effects on the thermal conductivity enhancement of nanofluids.

Substantial increases in thermal conductivity are seen for all measured nanofluids, with thermal conductivity enhancement up to 17.5% observed for nanotube loading at 1.0 vol% in EG (Lifei Chen 2008). The experimental data clearly indicate that the ratios of the enhancements increase monotonously with the volume fraction of TCNTs. For all the measured volume fractions, the thermal conductivity enhancement ratios of DW based nanofluids are smaller than the corresponding values of EG based nanofluids. TCNT suspensions present a similar behaviour (Huaqing Xie 2009). The volume fractions and the morphologies of TCNTs play dominant roles on the thermal transport in the nanofluids. The increases in thermal conductivity are seen for all the measured nanotube suspensions, with thermal conductivity enhancement ratio increasing with CNT loading.

The theory predicts highest enhancement for higher volume fraction and experimental results show highest enhancement for lower volume fraction due to good dispersibility. Therefore for higher concentration of CNTs in nanofluids ( f >0.01 vol%) the model has to incorporate the effective volume fraction term ( feff) for effective in thermal conductivity considering third surfactant phase (Vijay S. Raykar 2010). The interfacial resistance term of the static analysis has less influence on the overall thermal conductivity enhancement thus revealing the demand for inclusion of temperature term. From (Min-Sheng Liu 2005) the results indicated that CNT based EG suspensions have noticeably higher thermal conductivities than EG base fluids. Conductivity of CNT nanofluid is enhanced approximately linearly with the volume fraction of CNT. The rates of increase are, however, different for different base fluids. However, the other investigation that involves the effect of volume concentration to thermal conductivity will be finding in the other previous researcher with different type of method, CNT, based fluid and different amount of volume loading.

Using the cylindrical nanoparticles containing nanotube in engine oil suspension by Ebrahimi et al. (Sadollah Ebrahimi 2007), show the enhancement normalized thermal conductivity due to increasing in nanoparticles volume fraction. Xie et al. (Huaqing Xie 2003) using TCNT nanofluids show the enhancement up to 19.6% of thermal conductivity for nanotube loading at 1.0vol.% in decene (DE) rather than compare TCNT in DW and TCNT in EG. The result also indicated for MWCNT based EG and MWCNT based synthetic engine oil at 1.0vol.% and 2.0vol.% in volume fraction where the thermal conductivity enhancement up to 12.4% and 30% (MinSheng Liu 2011).

6.2.5. Effect to the Time

There are many researches done on the effect of various typical of ultrasonication time to the thermal conductivity. A sample was made using MWCNT with diameter between (60-100nm) and length between (0.5-40Î¼m) because these MWCNTs produced the greatest thermal conductivity enhancement for sample after ultrasonication times of 10-40 min. It was observed that the enhancement obtained after 10 minutes of ultrasonication time was 8.4%. Further evidence to support the local aggregation hypothesis is found from the time dependent magnetic results (Jesse Wensel 2008). In the presence of a magnetic field, the thermal conductivity shows very interesting behaviour. The thermal conductivity initially increases with time but eventually reaches a peak. With more time in the magnetic field, the particles gradually form clumps of Fe2O3 particles and clumps of CNTs, thus, decreasing the thermal conductivity as these clumps precipitate from the solution. This is attributed to the possible breaking of the aggregation under the long-time strong external magnetic force. More interestingly, after the fluid was removed from the magnetic field and resonicated for a few minutes, the thermal conductivity will return to the normal value back.

It is really different from Nasiri et al. (A. Nasiri 2012) where the thermal conductivity of all structures decreases in time especially by the first 10 days after the nanofluid preparation, but the reduction rate also decreases with time. It is worth noting that no settlements were observed during the first 400 h after nanofluid preparation, so the fraction of contained CNTs remained unchanged. However, the thermal conductivity reduction with time indicates that the CNT structures are agglomerated gradually by time. It shows that not only the thermal conductivity of all structures increases with an increase in temperature, but also it is shown that nanofluids composed of smaller structures experiences a greater enhancement than with larger structures.

6.2.6. Effect of Particle Size

Some literature is available about the particles size effect over nanofluids thermal conductivity. The researcher reported that the thermal conductivity will increase due to the increasing in particle size. Commonly CNT structures with smaller diameter illustrate greater enhancement in thermal conductivity with increase in nanoÂlayer thickness especially when particle diameter is less than 10nm. In a small particle size range, the effects of particle size and nano-layer thickness become much more obvious, which implies that influence nano-layer structure might be an effective method to offer highly thermally conductive nanofluids.

The cumulates means of nanofluids obtained 2 month after preparation by the Zetasizer Nano instrument were just above 200 nm which shows the good stability and low agglomeration rate of the nanofluids (A. Nasiri 2012). Yu et al. (W. Yu 2008) in their final conclusion for the intermediate size particle expend high in thermal conductivity, hence the result in thermal conductivity of SWCNT/water is higher that MWCNT based water nanofliuds.

By refer to the Jiang et al. (Weiting Jiang 2009) when the thermal conductivities of CNT nano-refrigerants using small diameter are much higher than those of CNT nano-refrigerants using the large diameters. The smaller diameter means the larger specific surface of CNTs and the larger specific surface means more obvious Brownian movement which is regarded as an important factor to increase the thermal conductivity of nanofluid (Kalpana Tumuluri 2011; Zeinab Talaei 2011). Moreover, larger specific surface means that there are more liquid molecules close to the surface of CNT if the volume fractions of CNTs are the same. The liquid molecules can form a layer structure, called interfacial layer. The interfacial layer on the nanoparticle surface can increase the thermal conductivity of nanofluids. Hence it can be interpreted that the smaller diameter means the thicker interfacial layer and the greater thermal conductivity enhancement.

In this paper, Fei Chan 2012 developed a theoretical model for explaining the enhancement in the effective thermal conductivity of nanotubes (with cylindrical shape) for use in nanotube in fluid suspensions. Their theoretical model shows that with the decrease of nanotube diameter, the thermal conductivity increases if the thickness of nanolayers increases. They provide a good estimation for the nanolayer's thickness which plays an important role in increasing the thermal conductivity, which we can increase, nanolaye thickness with surface treatment of nanoparticle. Chen et al. (Lifei Chen 2010) conclude about the average particles size where MWCNT are much higher rather than DWCNT and SWCNT. Hence it wills notify the smaller diameter means the larger specific surface of CNT which produce obvious Brownian motion to increase the thermal conductivity performance.

Table 7

The thermal conductivity measurement technique/method and stability inspection instrument

No.

Researcher

Type of CNT

Measurement Technique/Method

Stability Inspection Instrument

1

(H. Xie 2003)

MWCNT

The Transient Hot Wire Method

(TEM)

2

(Chibante 2005)

SWCNT and MWCNT

The Transient Hot Wire Method

(SEM) and (TEM)

3

(Min-Sheng Liu 2005)

MWCNT

The Transient Hot Wire Method

(SEM)

4

(Y. Hwang 2007)

MWCNT

The Transient Hot Wire Method

## -

5

(Brian Wright 2007)

SWCNT

Hot Disk Thermal Constant Analyzer

(SEM) and (TEM)

6

(J. Glory 2008)

MWCNT

The Steady State Method using Coaxial-Cylinder Cell

(SEM) and (TEM)

7

(Tushar Sharma 2008)

MWCNT

Chemical Reduction Technique

(SEM) and (TEM)

8

(Lifei Chen 2008)

MWCNT

The Transient Hot Wire Method

(TEM)

9

(Weiting Jiang 2009)

CNT

The Transient Plane Source (TPS)

(TEM)

10

(Huaqing Xie 2009)

MWCNT(PCNT and TCNT)

The Transient Hot Wire Method

(TEM)

11

(Milanova 2009)

SWCNT

The Transient Hot Wire Method

(TEM)

12

(Ramaprabhu 2009)

MWCNT

KD2 Pro Thermal Properties Analyzer

(TEM)

13

(Mark Horton 2010)

SWCNT

Hot Disk Thermal Constant Analyzer

(SEM) and (TEM)

14

(A. Amrollahi 2010)

MWCNT

KD2 Pro Thermal Properties Analyzer

(SEM)

15

(Majid Emami Meibodi 2010)

MWCNT

KD2 Pro Thermal Properties Analyzer

(TEM)

16

(Vijay S. Raykar 2010)

CNT

The Transient Hot Wire Method

(SEM)

17

(Zeinab Talaei 2011)

MWCNT

KD2 Pro Thermal Property Meter

(SEM)

18

(Kalpana Tumuluri 2011)

MPCM and MWCNT

The Transient Hot Wire Method

## -

19

(Jacobi 2012)

MWCNT

KD2 Pro Thermal Properties Analyzer

(SEM) and (TEM)

20

(Zhaoguo Menga 2012)

CNT

KD2 Pro Thermal Properties Analyzer

(TEM)

21

(Leyuan Yu 2012)

MWCNT

KD2 Pro Thermal Properties Analyzer

(TEM)

22

(Sivasankaran Harish 2012)

SWCNT

The Transient Hot Wire Method

(TEM)

23

(Binglu Ruan 2012)

MWCNT

KD2 Pro Thermal Properties Analyzer

(SEM) and TEM)

24

(A. Nasiri 2012)

SWCNT, FWCNT,DWCNT and MWCNT

KD2 Pro Thermal Properties Analyzer

(SEM) and (TEM)

25

(C.A. Nieto de Castro 2012)

MWCNT

KD2 Pro Thermal Property Analyzer

(TEM)

Note: MPCM, (SEM) and (TEM) refer to the Microencapsulated Phase Change Materials, Scanning Electron Microscopy and Transmission Electron Microscope

Table 8

Summary result for enhancement in thermal conductivity for various types of CNT,cyluindrical particles and based fluids

Year

Author

Type of Cylindrical

Volume Concentration

(wt %)

Size

Ultrasonication Time (min)

Temperature (Â°c)

Outer Diameter (nm)

Inner Diameter (nm)

Length (nm)

2007

(Y. Hwang 2007)

MWCNT

1.0

1030

1050

## -

## -

## -

2008

(L. Chen 2008)

MWCNT

1

15

30

## -

## -

## -

2011

(Kalpana Tumuluri 2011)

MWCNT

1

60Â100

1Â2

## -

20

32

60Â100

0.5Â40

## -

20

32

10Â30

1Â2

## -

20

33

10Â30

0.5Â40

## -

40

34

2012

(Binglu Ruan 2012)

MWCNT/Water

0.24

10-30

5-10

10-30

## -

20

MWCNT/EG

0.24

10-30

5-10

10-30

## -

20

## Viscosity Characteristic of Carbon Nanotube Nanofluids

Phuoc et al. (Tran X. Phuoc 2011) in their investigation of viscosity measurement for aqueous nanofluids containing MWCNT stabilized by different chitosen weight fraction were perform using Brookfield R/S Coaxial Cylinder Rheometer (RS115LS, Brookfield Engineering). The device can provide rotational steady state control shear stress or controlled shear rate measurement. Hence from their investigation they observed that dispersing chitosan into deionised water (DW) will increase the viscosity significantly.

Chen et al. (Lifei Chen 2008) also in their investigation of viscosity measurement using viscometer (0.5Â1000mPa s) use cationic gemini surfactant (12Â3Â12,2BrÂ1) and MWCNT with specific purity, length and diameter as it materials. It is also discover by Ye et al. (Hongfei Ye 2011) when they use "EyeringÂMD" method to examines the size effect on the water viscosity of CNT which obtained by the MD simulation were was employed I the article of openedÂsource code lammps. They consider the armchair SWCNT of diameter in a specific wide rage.

7.1. Theoretical Study

To measure the viscosity of nanofluids, normally use TA instruments ARÂG2 rheometer. There are some existing theoretical formulas to estimate the viscosity of CNT. The viscosity has been reported to be consistent with the mixing theory. Table 9 shows the several theoretical model of viscosity publish in the several literatures. Brickman formula is the most acceptable formulas among researchers where the particle concentration must be less than 4%. It is continued using the Krieger and Dougherty formula where covering full range of particles volume fraction. Chen et al. afterword modified Krieger and Dougherty formula where include aa and a is the radii of aggregate and primary particles and D is the fractal index. Farnken and Acrivos formulate the new model considering ðœ™m as the maximum particles volume fraction.

Table 9

Conventional models of viscosity of solid/liquid suspensions

Researcher

Expression or Models

Brickman (J. 1952)

Krieger and Dougherty (I.M. Krieger 1959)

Chen et al. (H. Chen 2007)

Franken and Acrivos (N. Frankel 1967)

7.2. Experiment Study

Reports on viscosity of nanofluids containing CNT have not been consistent and less investigation rather than thermal conductivity and there were limited studies on rheological behaviour of CNT nanofluids. The rheological is important where provide a knowledge on the microstructure under static and dynamic condition. Newtonian or non-Newtonian of nanofluids is depending on the viscosity. Latest literature have performed that the viscosity of nanofluids is increased as a result of the addition of nanoparticles.

7.2.1. Effect of Temperature

Not all the researcher has been investigates the effect of temperature to the viscosity. The present authors have shown that the enhancement of shear rate in viscosity of nanofluids increases even more at elevated temperature. For Chen et al. (Lifei Chen 2008) explained the surfactant is keep constant at different weight percentage concentrations using (0.6wt%, 1.8wt% and 3.6wt% at room temperature), the viscosity of MWCNT suspension decrease with increase of temperature from 6-64Â°C. Cationic gemini surfactant (12Â3Â12, 2BrÂ1) was employed as dispersant. It is different when the temperature is setting where the value of viscosity will show the magnification with increase of cationic gemini surfactant (12Â3Â12, 2BrÂ1) content. At lower temperature more surfactant molecules are superfluous when MWCNT with 3.6wt% are preparing at room temperature. It is also follow by Y. Ding et al.

In generally Phuoc et al. (Tran X. Phuoc 2011) observe dispersing chitosan into DW will increase viscosity. Furthermore, if the weight percentage is increasing as well as the concentration is high, the resultant solution will behave as a nonNewtonian. It will call as a nonNewtonian fluid if the viscosity of the fluids is change with an increase in shear rate. Hence afterword this will affect due to de-agglomeration or magnification of CNT bundles with increase in shear rate as seen in other nonNewtonian fluids.

Tumuluri et al. (Kalpana Tumuluri 2011) show the viscosity was measured for the 60100 nm (diameter) and 0.5 40 Î¼m (length) MWCNT nanofluid with ultrasonication time of 10 min because this was the group that showed the greatest enhancement in thermal conductivity in the range between 2832 Â°C range. It can be concluded that the MWCNT fluid shows a slight shear thinning (non-Newtonian) behaviour. However, viscosity remains more or less constant in the selected temperature range. The viscosity of MWCNT fluid is observed to be higher than that of water (M. Fakoor Pakdaman 2012). In order to investigate the rheological behaviour of the utilized nanofluids, it is essential to see group they are classified as Newtonian or non-Newtonian type. It is clear that if shear stress of the fluid increases linearly with shear rate, the utilized nanofluid will be categorized under Newtonian type. The linear relation between the shear stress and shear rate ensures the Newtonian behaviour of the 0.4 wt.% nanofluid. It noticed that the kinematic viscosity at 0.4wt.% and temperature at 40Â°C of nanofluids is 67% higher than that. Moreover available correlations for predicting the kinematic viscosity are reliable for low bulk-fluids temperature (40-70Â°C).

According to the (Binglu Ruan 2012) the kinematic viscosity of water based test fluids at 20 Â°C will be explained. Prior to the viscosity measurement of nanofluids, the viscosity of water was measured and the average deviation was less than 2%. The addition of 0.18 vol.% gum arabic in water resulted in a 25.4% increase in viscosity. With the addition of 0.24 vol.% MWCNTs, and after sonication, the viscosity of the nanofluidcontainaing (WB#1) reached a maximum increase of 29.4% compared to that of water. After dilution, the increase in viscosity of nanofluids containing (WB#2 and WB#3) was almost half of that before their dilution. The dynamic viscosity of the EG based test fluids 20 Â°C, where it can be seen that the viscosity of ethylene glycol and a mixture of EG and gum arabic behave as Newtonian fluids. The viscosity of EG was increased by around 35% by addition of gum arabic.

The viscosity of CNT nanofluids as a function of shear rate was measured under various conditions with the same pH concentration and surfactant (Yulong Ding 2006). A clear shear thinning behaviour is seen under all conditions. Hence at a given shear rate, the viscosity of nanofluids increases with increasing CNT concentration and decreasing temperature. The important implication to CNT nanofluids flowing through the tubular geometry used in this work as the shear rate at the wall region is higher than that at the core region, hence lower viscosity at the wall region and better lubrication effect. The important implications to heat transfer as the heat transfer coefficient depends on the flow behaviour. There may be doubts that the shear thinning behaviour is due to the presence of Gum Arabic (GA) dispersant. A few rheological experiments were therefore carried out on GA solutions. The shear thinning behaviour at low shear rates but slight shear thickening is seen at shear rates is greater. The gap is narrowed down at high shear rates but the difference is still several-folds. This suggests that the presence of GA affects little on the viscosity of CNT nanofluids at low shear rates but may play a role at high shear rates (Bahadir Aladag 2012).

7.2.2. Effect of Weigh Percentage/Concentration

Yang et al. (Ying Yang 2006) study the dispersant concentration using MWCNT. The dispersions with highest and lowest dispersant concentrations are strongly sheared thinning, while the lowest dispersion behaves like a Newtonian fluid. At lower dispersant levels, less polymer molecules are adsorbed to the carbon surface and the protection toward agglomeration is reduced. At higher dispersant levels, bridging flocculation can occur between polymer chains. Agglomerates formed by either mechanism have great effects on dispersion viscosity at low shear stress. The agglomerates can be destroyed by the fluid motions under high shear stress. Hence at a given shear rate, the viscosity of nanofluids increases with increasing CNT dispersion concentration.

7.2.3. Effect of Time

The rheological viscosity behaviour of MWCNT based EG nanofluids after different sonication times were recorded before the nanofluid viscosity measurements. It is explained that the dynamic viscosity change with the shear rate for pure EG, however, the results for carbon nanotube suspensions displayed a shear thinning behaviour where the higher value in shear rate will decrease the viscosity of the nanofluid (Jacobi 2012). When comparing the rheological behaviour of samples subjected to different sonication times, it is found that the nanofluid with the sonication time of 40 min has the highest viscosity, and its viscosity decreased dramatically with an increase in shear rate. However, the viscosity of the sample with the sonication time of 1,355 min displays a more flat viscosity variation with an increasing shear rate. Finally, at higher shear rates, its viscosity approached that of the base fluid.

7.2.4. Effect of Particle Size

The intention of this study is to observe the size effects on the water viscosity (Hongfei Ye 2011). Here, the size effect on the viscosity of the confined water implies the influence of the diameter of SWCNT. By referring to this research they illustrate the variation of the relative amount of the hydrogen bonds of water confined in SWCNT with the diameter. Several remarkable increments can be found in at 25Â°C and 52Â°C, which are also consistent with the anomalous increments in the relative viscosity. While the relative amount of the hydrogen bonds slightly decreases with increasing temperature, which is in contrast to the trend of the relative viscosity. At the end, the relative viscosity of water inside the SWCNT increases with increasing particle size.

7.2.5. Effect of Volume Fraction

It is refer to the Chen et al. (Lifei Chen 2008), the ratios of the viscosity of the CNT nanofluid (Î·) to the corresponding value of the base fluid (Î·0) are shown in this investigation. The base fluids of all the nanofluids are DW. At low volume fractions (ðœ™< 0.004), nanofluids have lower viscosity than the corresponding base fluids due to lubricate effect of nanoparticles. When the volume fraction is higher than 0.004, the viscosity increases with nanoparticle loadings. When the temperature is higher than 55Â°C, Î·/Î·0 appears to increase substantially with the temperature. Further investigation is needed to clarify the phenomena to investigate more about effecting of volume fraction.

## Density and Specific Heat

Previous investigator has been measure the density of different nanofluids containing different type of nanoparticle. Pakdaman et al. (M. Fakoor Pakdaman 2012) was using Pak (B. Pak 1998) propose equation, so the density of nanofluid will be known in this Eq. (5). This equation have been choose based on experimental result and lest square method for the based fluid at different temperature and the values calculate in Eq.(5) (M. Fakoor Pakdaman 2012). The density of nanofluid will increase and decrease due to the increase and decrease in the volumetric concentration of the particle and temperature due to the effect on the nanofluid. The model is one which is analogous to the mixing theory and the density of a nanofluid is expressed as:

ðœ™ (5)

Where the meaning of the symbol are Ïnf = density of nanofluid, Ïbf = density of base fluid, Ïs = density of solid particles, ðœ™ = volume concentration. The main focus that always been investigate is thermal conductivity follow by viscosity of nanofluids. Typically, these nanofluids properties will increase in thermal conductivity, viscosity and density except for the specific heat which decreases (M. Chandrasekara 2012). Knowing that the nanofluids specific heat is smaller than that of the based fluid whichs implies that for the same temperature increment, heat energy is needed is lesser for nanofluids compare to the based fluids. The simplicity of the models have been applied in the experimental by the researchers (Lee J 2007) and numerical nanofluids which is:

(6)

It is known that the knowledge of specific heat capacity is very important in determining other heat transfer properties, flow features as well as enthalpy calculations in various processes simulations. There was little increase in specific heat capacity of ionanofluids with increasing loading of MWCNT. Nonetheless, any increase in heat capacity of such suspensions or fluids is of great importance for their practical applications as heat transfer fluids (C.A. Nieto de Castro 2012).Typically, the nanofluid's specific heat is smaller than that of the base fluid which implies that for the same temperature increment, heat energy needed is lesser for nanofluid compared to base fluid. In the absence of available experimental data, the following two models have been extensively applied in the experimental and numerical nanofluid investigations to find the specific heat of nanofluid (J. 2006; Avsec J 2007).

(7)

According to this case there are no experimental data are available. Both expressions can be considered equivalent and either one maybe used to estimate nanofluids specific heat. The secondmodel is based on thermal equilibrium mechanism and the specific heat of a nanofluid is present as:

(8)

Pak and Cho (B. Pak 1998) model always been cites by a number of researchers which heat capacity concept will be seen in this Eq.(8) and volume fraction concept in Eq.(7).it can be classifying as the heat capacity, ðœ™ is the volume fraction, ðœŒ is the density, bf is referring to the based fluids and lastly p is referring to the properties of the nanoparticles. Hence for both model it can be clear that specific heat decrease with increasing nanoparticle concentration.

(9)

(10)

The changes in specific heats are modest compared to the changes in the viscosity and thermal conductivity of nanofluids due to the addition of the same volume concentration of nanoparticles. Using Vijjha and Das experimentation as the temperature of the nanofluid increases, the effective specific heat also increases moderately indicating that nanofluids possess slightly better thermal capacity at higher temperature. The specific heat capacities of nanofluids are different from that of base fluid and increase with the size of nanoparticles decrement. The high specific interfacial area of nanoparticle can absorb liquid molecules to its surface and form liquid layers, which will reversely constrain nanoparticle and turns its free boundary surface atoms to be non-free interior atoms. This effect will also enhance the specific heat capacity of nanofluid.

## Pool Boiling Heat Transfer

Past literature exhibit the investigation about pool boiling heat transfer of nanofluid (Kandlikar 2001; Scoot G. Liter 2001 ; Sarit K. Das 2003; Peter Vassallo 2004 ; In Cheol Bang 2005). Kandlikar (Kandlikar 2001) investigation is to develop theoretical model to predict Pool boiling CHF (Critical Heat Flux) by including the non-hydrodynamic aspect of surface-liquid interaction through the dynamic receding contact angle, surface orientation, and sub cooling effect. Knowing that nanofluids with high critical heat fluxes have the potential to provide the required cooling such as in military vehicles, military system, high power laser diodes and also submarines. Based on the effect of heater thermal properties, CHF will increase due to increase in thermal conductivity and increase in the heat capacity per unit surface area. By refer to the Das et al. (Sarit K. Das 2003) in reversing about considering the boiling heat transfer characteristics of Al2O3 based water nanofluids under atmospheri