Applied Thermal Engineering 94 (2016) 350–354
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Applied Thermal Engineering j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / a p t h e r m e n g
Silicon carbide nanowires suspensions with high thermal transport properties Wei Yu, Mingzhu Wang, Huaqing Xie *, Yiheng Hu, Lifei Chen College of Engineering, Shanghai Second Polytechnic University, Shanghai, 201209, China
H I G H L I G H T S
• • • •
The ethylene glycol suspensions containing SiC nanowires were prepared. The thermal conductivity of SiC/EG suspensions is signiﬁcantly improved. The large aspect ratio of SiC nanowires favors thermal conductivity enhancement. The experimental data are in reasonable agreement with Hamilton–Crosser model.
A R T I C L E
I N F O
Article history: Received 28 August 2015 Accepted 24 October 2015 Available online 2 November 2015 Keywords: Silicon carbide (SiC) nanowires Suspensions Large aspect ratio Thermal conductivity
A B S T R A C T
Nanoﬂuids have a broad prospect for thermal management applications in many ﬁelds. In this paper, ethylene glycol (EG) suspensions containing silicon carbide (SiC) nanowires were prepared by mechanical mixing. The average thermal conductivity of suspensions with SiC nanowires is greatly improved compared with that of pure EG, and it increases with the volume fraction of SiC nanowires. When the SiC loading is 5.0 vol.%, the thermal conductivity of the suspension was 0.443W/mK, increasing 67.2% with respect to pure EG. There is no obvious temperature dependency for the thermal conductivity enhancement ratio. These experimental results are in reasonable agreement with predicted values of Hamilton–Crosser model. The research conﬁrms that the shape factor of SiC has a critical effect on the effective thermal conductivity of suspensions. Meanwhile, it validates that the SiC nanowires have stronger ability to enhance thermal conductivity of suspensions than the other shapes. It is due to the large aspect ratio of SiC nanowires, which can easily form bridges between them, known as conductive network. The formation of random bridges or networks from conductive particles facilitates phonon transfer, leading to high thermal conductivity. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction In order to improve the thermal conductivity of heat transfer ﬂuids, the most effective approach is using thermal conductive particles as additives, including metal, metal oxide, graphite and carbon nanotubes, etc. However, such suspensions containing particles with size ranging from micrometers to millimeters are ordinarily unstable and prone to clogging systems with small channels [1,2]. Choi and Eastman  ﬁrst proposed the concept of nanoﬂuid in 1995; that is, in a certain way, the proportion of nano-sized metal or metal oxide particles is added to a liquid to form a class of new heat stable ﬂuid with relatively high thermal conductivity. The rapid development of nanotechnology has permitted uniformly stable nanoﬂuids to be a reality. Thus far, nanoﬂuids, used as novel heat transfer working ﬂuids, have broad application prospects in heat transfer
* Corresponding author. Tel.: +86-21-50214461; fax: +86-21-50214154. E-mail address: [email protected]
(H. Xie). http://dx.doi.org/10.1016/j.applthermaleng.2015.10.116 1359-4311/© 2015 Elsevier Ltd. All rights reserved.
ﬁelds, such as power generation, chemical production, manufacturing, transportation, and many other facets of modern life [4–8]. In the past two decades, many researchers [4–7] have demonstrated that nanoﬂuids, containing a small amount of metal or nonmetal nanoparticles, exhibit substantially enhanced thermal conductivities in comparison to those of the base ﬂuids. The nanosized particles, such as Cu [9,10], Al2O3 , CuO , MgO , ZnO  CNT  and graphene [16,17], have been used as ﬁllers to improve the thermal conductivity of nanoﬂuids based on water, glycol or oil. In essence, nanoﬂuid is a mixture of base ﬂuid and nanoparticles. According to the theories of the effective thermal conductivity of mixtures, such as the Maxwell model , Hamilton and Crosser model , and Davis model , the size, shape and intrinsic thermal conductivity of nanoparticles have a great inﬂuence on the thermal conductivity enhancement of nanoﬂuids. In this paper, silicon carbide (SiC) nanowires are selected to prepare nanoﬂuids due to their high thermal conductivity and large aspect ratio, which is favorable to enhance the effective thermal conductivity. Timofeeva et al.  investigated the effect of average
W. Yu et al./Applied Thermal Engineering 94 (2016) 350–354
Fig. 1. SEM images of SiC nanowires (a) at low magniﬁcation and (b) at high magniﬁcation.
particle size on basic macroscopic properties and heat transfer performance of α-SiC/water nanoﬂuids. It suggested that nanoﬂuids with larger particles exhibit higher thermal conductivity and lower viscosity because of the smaller solid/liquid interfacial area of larger particles. They also  investigated base ﬂuid and temperature effects on the heat transfer eﬃciency of SiC in ethylene glycol (EG)/ H2O and H2O nanoﬂuids. Adding SiC nanoparticles to an EG/H2O mixture could signiﬁcantly improve the cooling eﬃciency. Yu et al.  reported SiC/water nanoﬂuid with 50–60% increase of heat transfer coeﬃcient above the base ﬂuid when compared on the basis of constant Reynolds number. Manna et al. , Hosseini et al.  and Xie et al. [26,27] also investigated the effect factors on the thermal conductivity of nanoﬂuids containing SiC, and their results indicated signiﬁcant increase in thermal conductivity. To further investigate the effects of shape and size of SiC on the thermal conductivity of suspensions, the SiC nanowires with high aspect ratio were added to EG to prepare SiC-based suspensions. The experimental thermal conductivity data were compared with the results of suspensions containing SiC nanoparticles with other shapes and expected values of theoretical model.
3. Results and discussion 3.1. Characterization of SiC nanowires The shape and size of SiC nanowires were observed by ﬁeld emission scanning electron microscope, as shown in Fig. 1. As seen in Fig. 1a and b, the SiC exhibits long straight wire-like or short bamboolike structures. The surface of long straight wire-like SiC is very smooth, while the short bamboo-like structure resulted from corrosion of hydroﬂuoric acid in puriﬁcation process. The diameter of SiC nanowires varies over a wide range from 0.2 to 1 μm and the length is 3–40 μm. The crystallinity and crystal phases of the sample were characterized using X-ray diffractometer. Fig. 2 shows the XRD pattern of the SiC nanowires, which shows six obvious and sharp diffraction peaks at 2θ = 33.6°, 35.8°, 41.4°, 60.0°, 71.8° and 75.5°, respectively. Among these peaks, the peaks indexed as (111), (200), (220), (311), and (222) correspond to the different facets of face-centered cubic β-SiC (JCPDS 74–1302), and the small peak indexed as (SF) resulted from the stacking faults . Besides these peaks, no other impurities are found in the XRD pattern.
The SiC nanowires provided by Changsha Sinet Advanced Materials Co., Ltd., China, were used without further treatment. The morphology and crystal structure of SiC nanowires were characterized by ﬁeld emission scanning scope (SEM) (S4800, Hitachi, Japan) and X-ray diffractometer (XRD) (D8 Advance, Bruker, Germany), respectively. The EG with analytical grade was purchased from Sinopharm Chemical Reagent Co., Ltd., Shanghai, China, and was used without further puriﬁcation. The suspensions with different loading of SiC nanowires were prepared by mechanical mixing SiC nanowires with EG using a planetary mixer/deaerator (Mazerustar KK-250S, Kurabo, Japan). The effective thermal conductivity of suspensions was measured using a thermal conductivity analyzer (C-Therm TCi, C-Therm Technologies Ltd., Canada), which is based upon the modiﬁed transient plane source principle. In order to keep the temperature constant, the test system including test samples was placed in constant temperature and humidity incubator (Shanghai Boxun Industry & Commerce Co., Ltd Medical Equipment Factory). The accuracy of temperature control in the incubator is ± 1 °C. All the thermal conductivity measurements of the samples in the experiments were repeated at least ﬁve times to ascertain the accuracy of the experimental results.
2 (degree) Fig. 2. XRD pattern of SiC nanowires.
W. Yu et al./Applied Thermal Engineering 94 (2016) 350–354 90
Thermal conductivity (W/mk)
30 20 10
As is well known, the effective thermal conductivity of nanoﬂuids could be greatly affected by temperature. Fig. 3 shows the thermal conductivity of the SiC/EG suspensions with varying SiC nanowires volume fraction as a function of test temperature. The loading of SiC nanowires has an obvious effect on thermal conductivity of SiC/ EG suspensions at a deﬁnite temperature. The thermal conductivity of SiC/EG suspensions increases with volume fraction of SiC nanowires at the same temperature. Meanwhile, the thermal conductivity of SiC/EG suspension increases slowly with the test temperature rise at the same SiC nanowires loading. Timofeeva et al.  demonstrated that the viscosity of nanoﬂuids based on EG decreases with increasing temperature, resulting in violent Brownian motions of suspended SiC nanowires. The micro convection caused by the Brownian motions would help to enhance the thermal conductivity of the suspensions. It should also be noted that there is a similar trend in thermal conductivity of suspensions with and without SiC nanowires with increasing temperature. This is another factor to cause increase in thermal conductivity when the temperature is ascended. Moreover, it is worth noting that all the thermal conductivity linear slopes of SiC/EG suspensions are nearly constant. In order to study the separate role of SiC nanowires for thermal conductivity improvement, the thermal conductivity enhancement ratios of SiC/EG suspensions are calculated with respect to that of pure EG at the corresponding temperature. It shows no obvious temperature dependency for thermal conductivity enhancement ratio with different ﬁller loadings, as shown in Fig. 4. Δλ/λ0 represents the thermal conductivity enhancement ratio, where Δλ = λe–λ0, λe and λ0 represent the thermal conductivity of SiC/EG suspensions and the pure EG, respectively. As seen in Fig. 4, the thermal conductivity of suspensions with 1.0–5.0 vol.% SiC is greatly improved compared with base ﬂuid. It shows that at a temperature of 20 °C the thermal conductivity of suspensions with 1.0–5.0 vol.% SiC nanowires increases by 14.1%, 17.5%, 31.2%, 47.2% and 60.5%, respectively. Some groups have reported that the thermal conductivity enhancement of nanoﬂuids with nanomaterial increases at elevated test temperature [11,22]. Meanwhile, several groups have also reported that the thermal conductivity enhancement tendency of nanoﬂuids is not close to that of base ﬂuid, appearing almost constant for thermal conductivity enhancement ratio at elevated temperature [29,30]. In this study, the thermal conductivity en-
Fig. 4. Thermal conductivity enhancement ratios of SiC/EG suspensions as a function of temperature for varying ﬁller loading.
hancement ratios also show a constant trend broadly. The discrepancy indicates that many factors affect the thermal conductivity enhancement of nanoﬂuid, including the size and shape of particle, the ﬁller clustering and sedimentation, preparation processes, and so on. Fig. 5 shows the average thermal conductivity of SiC/EG suspensions with varying of SiC nanowires loading, where the average thermal conductivity is the average values of suspensions at different temperatures in certain ﬁller content. The experimental results show that the thermal conductivity of SiC/EG suspensions is signiﬁcantly improved compared with that of pure EG. The thermal conductivity of SiC/EG suspensions linearly increases with the increase of the fraction of SiC nanowires, which is consistent with the results reported by Xie et al. [26,27] about nanoﬂuid system containing nano-SiC and water or EG. Meanwhile, it can be seen that the thermal conductivity of suspensions with 5.0vol.% SiC loading is 0.443 W/mK, increasing 67.2% compared with that of pure EG (0.265 W/mK). Regression analysis of the recorded experimental data shows a linear ﬁt with an R2 value of 0.99104 expressed as:
Thermal conductivity (W/mk)
3.2. Thermal conductivity of suspensions with SiC nanowires
Temperature ( C)
Temperature( C) Fig. 3. Thermal conductivities of different SiC/EG suspensions as a function of temperature.
Experimental value Linear fit
Volume fraction of SiC nanowires(%) Fig. 5. Average thermal conductivity of suspensions with varying volume fraction of SiC nanowires.
Table 1 Parameters of different of SiC particles.
Average size Particle shape 100Δλ/λ0 (4.0 vol.%)
25 nm Sphere 15.2%
600 nm Cylinder 22.9%
6 μm Nanowire 52.2%
λe = 0.27 + 0.034φ where λe and ϕ are effective thermal conductivity of SiC/EG suspensions and volume fraction of SiC nanowires, respectively. The slope of linear ﬁtting equation is 0.034, and the intercept (0.27) is on the verge of the experimental thermal conductivity value of EG. 3.3. Comparison to theoretical prediction models The thermal conductivity of suspensions with SiC nanowires is compared with the thermal conductivity data about SiC nanoparticles . The paper investigated the effects of size and shape on thermal conductivity enhancement of suspensions with different SiC particles. Table 1 is the parameters of different SiC particles. It can be seen that the SiC particles used in that paper are spherical SiC (SiCsphere) and cylindrical SiC (SiC-cylinder), with an average particle size of 25 and 600 nm, respectively. The shape and size of SiC particles have a great inﬂuence on the thermal conductivity enhancement, proven by the results reported by Xie et al.  about suspension with SiC-spheres and SiCcylinders. At SiC loading of 4.0vol.%, the thermal conductivity enhancement of suspension with SiC-cylinders is 22.9% with respect to pure EG, which is larger than that of suspension with SiCspheres (15.2%). It is worth noting that the thermal conductivity enhancement of suspension with SiC nanowires is 52.2%, more than two times higher than that of suspension with SiC-cylinders. Lee et al. [31,32] have proved that the aspect ratio of ﬁller is more considerable that dictates the thermal conductivity of a composite. In this study, the SiC nanowires with large aspect ratio can easily form bridges between them, known as conductive network. The formation of random bridges or networks from conductive particles facilitates phonon transfer, leading to high thermal conductivity. Therefore, the SiC nanowires are more effective in enhancing thermal transfer properties than the SiC cylinders and SiC spheres with small aspect ratio. Regarding thermal conductive properties of nanoﬂuids, many scholars have put forward different theoretical prediction models. For the most part, thermal conductivity enhancement for nanoﬂuids follows the predictions of some models based on effective medium theory (EMT). Among them, there are two well-known models, that is, Maxwell model and Hamilton–Crosser (H–C) model. Maxwell model is an approach for computing the effective electrical conductivity of a random suspension of spherical particles . With preparation technology advancement of nanoparticles, a lot of nanoparticles with different shape have been synthesized, such as cylinder, ellipse and nanowire, making the Maxwell model not suitable for these non-spherical particles. In this connection, Hamilton and Crosser  developed a relatively complicated model to predict the thermal conductivity of suspensions containing micrometersized or millimeter-sized particles. Furthermore, the H–C model gives a better prediction for effective thermal conductivity of suspensions with non-spherical particles since it accounts for the shape of the particles. The Hamilton–Crosser model formula is given by
[λp λo + (n − 1) − (n − 1)φ (1 − λp λo )]λo λp λo + (n − 1) + φ (1 − λp λo )
Thermal conductivity enhancement(%)
W. Yu et al./Applied Thermal Engineering 94 (2016) 350–354
SiC-sphere (Ref. 27) SiC-cylinder (Ref. 27) SiC-nanowire H&C model: sphere H&C model: cylinder H&C model: nanowire
60 50 40 30 20 10 0
Volume fraction of filler (%) Fig. 6. Comparison of thermal conductivity enhancements of different suspensions with the predictions from Hamilton–Crosser model.
where λp is the effective thermal conductivity of heat conduction ﬁller, n is the empirical shape factor given by n = 3/Φ, and Φ is the sphericity. For the spherical and cylindrical particle, the sphericity (Φ) is 1 and 0.5, respectively. In fact, even for cylindrical particles, they always have different length and diameter. Therefore, n is an empirical scaling factor that takes into account the effect on different particle shapes. We can adjust n according to the morphology of different particles to highlight the importance of the shape factor . As a matter of fact, Yamada and Ota  have proposed a similar model based on the unit-cell model, which considers the discontinuous phase particle shape and dimension of principal axis direction. This model formula is given by
[λp λo + K − K φ (1 − λp λo )]λo λp λo + K + φ (1 − λp λo )
where K is the shape factor, K = 2Φ0.2 (lp/ld), lp and ld are the length and diameter of high aspect ratio particles, respectively. Compared with the H–C model, the shape factor K in the Yamada model is equal to (n−1) in the H–C model. Fig. 6 shows the comparison between the experimental results and calculated values from the H–C model with different n value. Xie et al.  reported that the shape factors of suspensions with SiC-sphere and SiC-cylinder are 3 and 6, i.e., the sphericity Φ is 1 and 0.5, respectively. The theoretical model predictions are in reasonable agreement with the experimental data. In this paper, the lp/ld is about 9, obtained through the data statistics and calculation; thus, the calculated n is about 14. When n = 14, the predicted curve of the H–C model is shown in Fig. 6. It can be seen that the prediction values are inosculated with the experimental data. Based on the experimental and theoretical prediction results in this study, the key role of ﬁller aspect ratio in the thermal conductivity enhancement of the suspensions is highlighted. At the same time, it could provide an approach to solve the poor heat transfer ratio of conventional heat transfer ﬂuids, that is, increasing thermal conductivity by dispersing ﬁllers with high aspect ratio in the base liquid. 4. Conclusions In conclusion, the thermal conductivity of suspensions, prepared by mechanical mixing of EG and SiC nanowires, was measured
W. Yu et al./Applied Thermal Engineering 94 (2016) 350–354
by using a thermal conductivity analyzer. The effect of temperature on thermal conductivity of suspensions was also investigated. The experimental results showed that the thermal conductivity of suspensions with SiC nanowires increased with SiC loading, which was greatly enhanced compared with that of pure EG. And the thermal conductivity of suspension with 5.0 vol.% SiC loading was 0.443 W/mK, increasing 67.2% with respect to pure EG. At the same time, there is no obvious temperature dependency for thermal conductivity enhancement ratio with different ﬁller loadings. The comparison results indicated that shape factor had a substantial effect on the effective thermal conductivity of suspension. Compared to SiC-sphere and SiC-cylinder, the SiC nanowires with large aspect ratio could easily form bridges between them, known as conductive network. The formation of random bridges or networks from conductive particles facilitates phonon transfer, leading to high thermal conductivity. Moreover, the experimental data were also compared to prediction from the Hamilton–Crosser model, showing a reasonable inosculation. Based on the results of our study, the shape factor plays an important role in the thermal conductivity enhancement of thermal conductive suspension. It could provide an approach to solve the poor heat transfer ratio of conventional heat transfer ﬂuids, that is, increasing thermal conductivity by dispersing ﬁllers with high aspect ratio in the base liquid. Besides thermal conductivity, the viscosity and long-term stability of this suspension are important in practical application as well. So the inﬂuence of shape factor on viscosity and long-term stability of thermal conductive suspension will be investigated systematically in our further research. Acknowledgements The work was supported by the National Natural Science Foundation of China (51476094, 51106093, 51306109), the Basic Research Foundation of Shanghai Science and Technology Committee (12JC1404300), Innovation Program of Shanghai Municipal Education Commission (14ZZ168 and 14cxy37), Program for Professor of Special Appointment (Eastern Scholar) at the Shanghai Institutions of Higher Learning and the key subject of Shanghai Second Polytechnic University (No. 4, Material Science and Engineering, XXKYS1401). Junchang Zhao is gratefully acknowledged for his help in the discussion part. References  C.W. Sohn, M.M. Chen, Microconvective thermal conductivity in disperse two-phase mixtures as observed in a low velocity Couette ﬂow experiment, J. Heat Transfer 103 (1981) 47–51.  A.S. Ahuja, Thermal design of a heat exchanger employing laminar ﬂow of particle suspensions, Int. J. Heat Mass Tran. 25 (1982) 725–728.  S.U.S. Choi, A.S. Eastman, Enhancing thermal conductivity of ﬂuids with nanoparticles developments and applications of non-newtonian ﬂows. Argonne National Laboratory Report ANL-84938, 1995.  A.R. Moghadassi, S.M. Hosseini, D.E. Henneke, Effect of CuO nanoparticles in enhancing the thermal conductivities of monoethylene glycol and paraﬃn ﬂuids, Ind. Eng. Chem. Res. 49 (2010) 1900–1904.  R. Azizian, E. Doroodchi, B. Moghtaderi, Effect of nanoconvection caused by Brownian motion on the enhancement of thermal conductivity in nanoﬂuids, Ind. Eng. Chem. Res. 51 (2011) 1782–1789.
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