ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
Prev
Next
|
|
|
Modified Maxwell model for predicting thermal conductivity of nanocomposites considering aggregation |
Wen-Kai Zhen(甄文开)1, Zi-Zhen Lin(蔺子甄)1, Cong-Liang Huang(黄丛亮)1,2 |
1. School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; 2. Department of Mechanical Engineering, University of Colorado, Colorado 80309-0427, USA |
|
|
Abstract The effect of nanoparticle aggregation on the thermal conductivity of nanocomposites or nanofluids is typically non-negligible. A universal model (Maxwell model) including nanoparticle aggregation is modified in order to predict the thermal conductivity of nanocomposites more accurately. The predicted thermal conductivities of silica and titania nanoparticle powders are compared first with that measured by a hot-wire method and then with those in previous experimental works. The results show that there is good agreement between our model and experiments, and that nanoparticle aggregation in a nanocomposite enhances the thermal conductivity greatly and should not be ignored. Because it considers the effect of aggregation, our model is expected to yield precise predictions of the thermal conductivity of composites.
|
Received: 05 May 2017
Revised: 12 June 2017
Accepted manuscript online:
|
PACS:
|
44.30.+v
|
(Heat flow in porous media)
|
|
44.35.+c
|
(Heat flow in multiphase systems)
|
|
Fund: Project supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 2015XKMS062). |
Corresponding Authors:
Cong-Liang Huang
E-mail: huang198564@gmail.com
|
Cite this article:
Wen-Kai Zhen(甄文开), Zi-Zhen Lin(蔺子甄), Cong-Liang Huang(黄丛亮) Modified Maxwell model for predicting thermal conductivity of nanocomposites considering aggregation 2017 Chin. Phys. B 26 114401
|
[1] |
Tang J, Wang H T, Lee D H, Fardy M, Huo H Z, Russell T P and Yang P 2010 Nano Lett. 10 4279
|
[2] |
Lin Z Z, Huang C L and Huang Z 2017 J. Nanosci. Nanotechnol. 17 1
|
[3] |
Dresselhaus M S, Chen G, Tang M Y, Yang R G, Lee H, Wang D Z, Ren Z F, Fleurial J P and Gogna P 2007 Adv. Mater. 19 1043
|
[4] |
Lin Z Z, Huang C L, Zhen W K, Feng Y H, Zhang X X and Wang G 2017 Nanoscale Res. Lett. 12 189
|
[5] |
Liu H, Li Z Y, Zhao X P and Tao W Q 2015 J. Nanosci. Nanotechnol. 15 3218
|
[6] |
Huang C L, Lin Z Z, Feng Y H, Zhang X X and Wang G 2015 Eur. Phys. J. Plus 130 239
|
[7] |
Li Z Y, Liu H, Zhao X P, and Tao W Q 2015 J. Non-Cryst. Solids 430 43
|
[8] |
Feng D L, Feng Y H and Shi J 2016 Acta Phys. Sin. 65 244401(in Chinese)
|
[9] |
Liu H, Li Z Y, Zhao X P and Tao W Q 2016 Int. J. Heat Mass Transfer 95 1026
|
[10] |
Zhang C B, Shen C Q and Chen Y P 2017 Int. J. Heat Mass Transfer 104 1135
|
[11] |
Yu W and Xie H 2011 J. Nanomater. 2012 435873
|
[12] |
Kulwinder K and Ranjan K 2016 Chin. Phys. B 25 056401
|
[13] |
Yu W, Xie H, Yin L, Zhao J, Xia L and Chen L 2015 Int. J. Therm. Sci. 91 76
|
[14] |
Rayleigh L 1976 Philos. Mag. 34 481
|
[15] |
Prasher R S and Phelan P E 1999 J. Heat Transfer 123 105
|
[16] |
Lotfizadeh S and Matsoukas T 2015 J. Nanopart. Res. 17 1
|
[17] |
Eapen J, Rusconi R, Piazza R and Yip S 2010 J. Heat Transfer 132 369
|
[18] |
Progelhof R C 1976 Polym. Eng. Sci. 16 615
|
[19] |
Choi C J and Roberts N 2016 Int. J. Therm. Sci. 104 13
|
[20] |
Siddiqui M U and Arif A F M 2016 Materials 9 694
|
[21] |
Huang C L, Feng Y H, Zhang X X and Wang G 2014 Eur. Phys. J. Appl. Phys. 66 67
|
[22] |
LotfizadehS and Desa T 2014 APL Mater. 2 066102
|
[23] |
Huang C L, Qian X and Yang R G 2017 EPL 117 24001
|
[24] |
Wang B X, Wang Zhou L P and Peng X F 2003 Int. J. Heat Mass Transfer 46 2665
|
[25] |
Li X, Park W, Chen Y P and Ruan X L 2017 J. Heat Transfer 139 022401
|
[26] |
Lin Z Z, Huang C L, Zhen W K and Huang Z 2017 Appl. Therm. Eng. 119 425
|
[27] |
Huai X L, Tao Y J and Wang W W 2006 Chin. Phys. Lett. 23 1511
|
[28] |
Xuan Y M and Li Q 2000 Int. J. Heat Fluid Fl. 21 58
|
[29] |
Zhao D L, Qian X, Gu X K, Jajia S A and Yang R G 2016 J. Electronic Packaging 138 040802
|
[30] |
Huang C L, Feng Y H, Zhang X X, Li J, Wang G and Chou A H 2013 Acta Phys. Sin. 63 026501(in Chinese)
|
[31] |
Ordonez-MirandaJ, Yang R G and Alvarado-GilJ J 2011 Appl. Phys. Lett. 98 233111
|
[32] |
Dornhaus R, Nimtz P D G and Richter W 1976 Solid-State Physics (Germany:Springer Verlag)
|
[33] |
Jiang W T, Ding G L, Peng H, Gao Y F and Wang K J 2009 HVAC & R Res. 15 651
|
[34] |
Hwng Y J and Ahn Y C 2006 Curr. Appl. Phys. 6 1068
|
[35] |
Machrafi H, Lebon G and Iorio C S 2016 Compos Sci. Technol. 130 78
|
[36] |
Lee S and Choi S 1999 J. Heat Trans.-T ASME 121 280
|
[37] |
Sim L C and Ramanan S R 2005 Thermochim. Acta 430 155
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|