Roundrobin test on thermal conductivity measurement of ZnO nanofluids and comparison of experimental results with theoretical bounds
 WookHyun Lee^{1},
 ChangKyu Rhee^{2},
 Junemo Koo^{3},
 Jaekeun Lee^{4},
 Seok Pil Jang^{5},
 Stephen US Choi^{6}Email author,
 KiWoong Lee^{1},
 HwaYoung Bae^{1},
 GyoungJa Lee^{2},
 ChangKyu Kim^{2},
 Sung Wook Hong^{3},
 Younghwan Kwon^{4},
 Doohyun Kim^{4},
 Soo Hyung Kim^{4},
 Kyo Sik Hwang^{5},
 Hyun Jin Kim^{5},
 Hyo Jun Ha^{5},
 SeungHyun Lee^{5},
 Chul Jin Choi^{6} and
 JiHwan Lee^{6}
DOI: 10.1186/1556276X6258
© Lee et al; licensee Springer. 2011
Received: 30 October 2010
Accepted: 25 March 2011
Published: 25 March 2011
Abstract
Ethylene glycol (EG)based zinc oxide (ZnO) nanofluids containing no surfactant have been manufactured by onestep pulsed wire evaporation (PWE) method. Roundrobin tests on thermal conductivity measurements of three samples of EGbased ZnO nanofluids have been conducted by five participating labs, four using accurate measurement apparatuses developed in house and one using a commercial device. The results have been compared with several theoretical bounds on the effective thermal conductivity of heterogeneous systems. This study convincingly demonstrates that the large enhancements in the thermal conductivities of EGbased ZnO nanofluids tested are beyond the lower and upper bounds calculated using the models of the Maxwell and Nan et al. with and without the interfacial thermal resistance.
Introduction
Nanofluids, a new class of fluids engineered by uniformly dispersing nanostructures such as nanoparticles, nanotubes, nanorods, and nanofibers, in base fluids, have heat and mass transport properties that are far superior to those of the base fluids. For example, a number of research groups presented surprising experimental findings that nanofluids significantly enhance thermal conductivities [1–8], convective heat transfer coefficient [9–13], and heat absorption rate [14]. Therefore, these novel nanofluids have the potential to become nextgeneration coolants and working fluids for innovative applications in industries such as energy, bio and pharmaceutical industry, and chemical, electronic, environmental, material, medical and thermal engineering among others [15, 16]. Nanofluids have thus attracted considerable interest worldwide. Hundreds of research groups, in both academia and industry, are exploring nanofluids. Most recently, the European Commission launched Nanohex [17], the world's largest collaborative project for the research and development of nanofluid coolants, bringing together 12 partners from academia and industry, ranging from small and mediumsized enterprises (SMEs) to global companies such as Siemens and Thermacore.
Of all the properties of nanofluids, thermal conductivity has sparked the most excitement and controversy. The anomalous enhancement of measured thermal conductivity [1–8], as compared with the predictions of the classical models, has generated excitement in both academia and industry. However, these data became controversial years later when no anomalous enhancement in thermal conductivity was observed [18–20]. These contradictory data have generated another controversy regarding the mechanisms of enhanced thermal conductivity in nanofluids. For example, a number of investigators proposed that new mechanisms are needed to explain anomalous enhancement [21–26]. However, some others [27–29] show that the thermal conductance mechanism in nanofluids is no different from that in binary solid composites or liquid mixtures, and that thermal conductivity data lie between the wellknown effective medium bounds of the Hashin and Shtrikman (HS) [30]. But, Murshed [31] pointed out that more systematic and careful investigations are needed to resolve the controversy over the mechanism of the enhanced thermal properties. Moreover, Schmidt et al. [32] showed that the thermal conductivity of nanofluids is greater than the HamiltonCrosser model [33].
These contradictory thermal conductivity data highlight the need for more controlled synthesis and accurate characterization of nanofluids. One way to reduce data inconsistencies due to differences in sample quality, such as particle size and size distribution including agglomeration, is to conduct roundrobin tests using identical test samples. Recently, Buongiorno et al. [34] launched an International Nanofluid Property Benchmark Exercise (INPBE) to resolve the inconsistencies in the database. They reported that the nanofluids tested in INPBE exhibit thermal conductivity in good agreement with the predictions of the effective medium theory for welldispersed nanoparticles.
There are several reasons for the good agreement. First, the nanofluids used in the INPBE were manufactured by twostep method with surfactant (Set 1) and chemical reduction method with several electrolytes (Set 2) or commercial products with various surfactants and electrolytes (Sets 3 and 4). Second, measurement uncertainty analysis is essential because the measured thermal conductivity data may have biases and random variation. However, most organizations using transient hot wire method (THWM) for measurement of the thermal conductivity did not perform the measurement uncertainty analysis.
So we thought that it would be interesting to produce nanofluids by a onestep physical method with no surfactant, perform measurement uncertainty analysis, and measure the thermal conductivity of the nanofluids using very accurate thermal conductivity apparatuses.
The objectives of this study are to conduct a roundrobin test on thermal conductivity measurements of three samples of EGbased ZnO nanofluids and compare the experimental results with theoretical bounds on the effective thermal conductivity of heterogeneous systems.
Different methods of sample preparation or even small differences in the sample preparation process can cause large differences in sample properties. Therefore, in this study, one laboratory synthesized all three samples of ZnO nanofluids using onestep pulsed wire evaporation (PWE) process to be described in "Synthesis of ZnO nanofluids" section. The roundrobin exercise involved five testlaboratories that have extensive experience in the thermal conductivity measurement of nanofluids. Each participant received identical samples of ZnO nanofluids and was asked to conduct the test within 2 weeks of receipt of samples. The five participating laboratories measured the thermal conductivity of the samples of ZnO nanofluids over a temperature range from 20 to 90°C using the THWM. The results were collected, analyzed, and plotted for comparison with several theoretical bounds [30, 35, 36] on the effective thermal conductivity of heterogeneous systems.
Based on the results of these roundrobin tests using identical test samples synthesized by onestep PWE method and accurate thermal conductivity apparatus with measurement uncertainty <1.5%, we clearly show that the large enhancements in the thermal conductivity of the EGbased ZnO nanofluids are beyond the lower and upper bounds of both the Maxwell model [35] with and without the interfacial thermal resistance and the Nan et al. model [36].
Experiments
Synthesis of ZnO nanofluids
Various synthesis procedures have been used for production of nanofluids. The PWE method is one approach to fabricate nanoparticles [37]. In this study we used the PWE method mainly because the process is simple to use, and it is not time consuming to produce nanofluids samples in enough quantity for the roundrobin measurements.
Previous studies on EG/waterbased ZnO nanofluids
Paper  Manufacturing method  Measurement method (Accuracy)  Base fluid  Surfactant  Comments 

Kim et al. [38]  Twostep  THW (1%)  Water/EG  Sodium dodecyl sulfate (SDS) of 0.05 M  Size dependence 
Yu et al. [39]  Twostep  STHW (1%)  EG    No temperature dependence 
Moosavi et al. [40]  Twostep  KD2 Pro (5%)  EG/glycerol  Ammonium citrate (dispersant:nanoparticle = 1:1 wt.%)  Temperature dependence 
Raykar and Singh [41]  Twostep  THW  Water  3, 5, and 7 mL of acetylacetone (acac) is added in type I, II, and III solutions  Temperature dependence without low vol. % 
Shen [42]  Commercial highvolume fraction dispersions in water with chemical dispersant (Nanophase)  THW  Water  Addition of chemical dispersants which is not disclosed by the company  Reverse size dependence 
Vajjha and Das [43]  Commercial 50% dispersion in water (Alfa Aesar)  Commercial device based on steadystate method^{a} (2.45%)  EG:W (6:4 wt.%)  Dispersant not clear  Temperature and size dependence 
Xie et al. [44]  Twostep    EG:W (45:55 vol.%)   
Thermal conductivity measurements and uncertainty analysis
In this study, four of the labs used a THWM developed in house to measure the thermal conductivity of EGbased ZnO nanofluids, and one of the five labs performed the thermal conductivity measurements using a commercial apparatus, LAMBDA (LAMBDA F5 Technology, Germany) with 1% error.
In order to obtain the accuracy of the transient hot wire apparatus, the measurement uncertainty analysis of the apparatus was performed by each laboratory as follows:
Results and discussion
Results of the roundrobin study and statistical treatment of data
Following the statistical data analysis procedures used in the INPBE study [34], we calculated the sample averages and the standard errors for all the thermal conductivity enhancement data. In Figure 4a, b, the sample average is shown as a solid line and the standard errors of the sample mean as dotted lines. As seen in Figure 4a, b, the experimental data obtained by the five participating labs lie within a narrow band about the sample average with only a few modest outliers. The data analysis shows that the standard errors of the sample mean for the 3.0 and 5.5 vol.% ZnO nanofluids samples are ±1.24 and ±3.95%, respectively.
Comparison of experimental results with theoretical bounds
The Hashin and Shtrikman (HS) bounds on the thermal conductivity of heterogeneous systems [30] have been used for nanofluids to show that the effective medium theory can explain the enhancement of nanofluids [27, 29]. The HS upper bound is given by Equation 5 and the HS lower bound is the classical Maxwell model as given by Equation 6. Recently, Buongiorno et al. [34] used Equation 6, the classical Maxwell model with negligible interface resistance, for the upper bound for nanofluids and Equation 7, the Maxwell model with interface resistance, for the lower bound for nanofluids.
where k_{f}, k_{p}, r_{p}, R_{b}, and φ are the thermal conductivities of base fluids and nanoparticles, radius of nanoparticles, interfacial thermal resistance, and volume fraction of nanoparticles, respectively.
Material properties used to calculate theoretical bounds
In addition, we used the generalized Maxwell model developed by Nan et al. [36] with and without interfacial resistance for the lower and upper bounds for nanofluids. The Nan et al. model is given in Equation 8.
where a_{ii}, a_{k}, L_{ii}, p, φ, and are the diameter of the ellipsoid, Kapitza radius, geometrical factors dependent on the particle shape, aspect ratio of the ellipsoid, volume faction, and equivalent thermal conductivities, respectively. R_{bd} is the interfacial thermal resistance, also known as thermal boundary resistance, or Kapitza resistance.
The comparisons of experimental results with theoretical models convincingly demonstrate that the large enhancements in the thermal conductivities of EGbased ZnO nanofluids are beyond the lower and upper bounds calculated using the models of Maxwell and Nan et al. with and without the interfacial thermal resistance the predictions of the effective medium theory for welldispersed nanoparticles.
Conclusions
Ethylene glycol (EG)based ZnO nanofluids containing no surfactant have been manufactured by onestep physical method using the PWE process. Roundrobin tests on thermal conductivity measurements of three samples of EGbased ZnO nanofluids have been conducted and the results have been compared with several theoretical bounds on the effective thermal conductivity of heterogeneous systems. The enhancements of the thermal conductivity of the ZnO nanofluids are beyond the upper and lower bounds of both the Maxwell model and Nan et al. model. Especially, the enhancement of the 5.5 vol.% ZnO nanofluids at 23 C is nearly 25%, while the enhancement predicted by the upper bound of the Maxwell model is at precisely 16.5%. Thus, the discrepancies in the thermal conductivity of the ZnO nanofluids tested in this study cannot be fully explained by the effective medium theory for welldispersed nanoparticles. Further research is needed to understand and resolve the controversies about contradictory data and new mechanisms of enhanced thermal conductivity in nanofluids.
Abbreviations
 EG:

ethylene glycol
 HS:

Hashin and Shtrikman
 INPBE:

International Nanofluid Property Benchmark Exercise
 PWE:

pulsed wire evaporation
 SMEs:

small and mediumsized enterprises
 TEM:

transmission electron microscopy
 THWM:

transient hot wire method
 ZnO:

zinc oxide.
Declarations
Acknowledgements
This work was supported by Energy and Resources Technology R&D Program (2008ECM 11P080000) under the Ministry of Knowledge Economy, Republic of Korea. We thank the participants in the roundrobin study for their substantial investments of both time and resources. This work could not have been accomplished without their passion and efforts.
Authors’ Affiliations
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