Skip to main content
Log in

Molecular dynamics simulation of thermal conductivity of Cu–Ar nanofluid using EAM potential for Cu–Cu interactions

  • Published:
Applied Physics A Aims and scope Submit manuscript

Abstract

Mechanism of heat conduction in copper-argon nanofluids is studied by molecular dynamics simulation and the thermal conductivity was obtained using the Green–Kubo method. While the interatomic potential between argon atoms is described using the well-known Lennard–Jones (L–J) potential, a more accurate embedded atom method (EAM) potential is used in describing the interatomic interaction between copper atoms. It is found that the heat current autocorrelation function obtained using L–J potential to describe the copper-copper interatomic interaction fluctuates periodically due to periodic oscillation of the instantaneous microscopic heat fluxes. Thermal conductivities of nanofluids using EAM potentials were calculated with different volume fractions but the same nanoparticle size. The results show that thermal conductivity of nanofluids are almost a linear function of the volume fraction and slightly higher than the results predicted by the conventional effective media theory for a well-dispersed solution. A solid-like base fluid liquid layer with a thickness of 0.6 nm was found in the simulation and this layer is believed to account for the small discrepancy between the results of MD simulation and the conventional effective media theory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. P. Keblinski, R. Prasher, J. Eapen, J. Nanopart. Res. 10, 1089 (2008)

    Article  Google Scholar 

  2. S. Lee, S.U.S. Choi, S. Li, J.A. Eastman, J. Heat Transf. 121, 280 (1999)

    Article  Google Scholar 

  3. J.A. Eastman, S.U.S. Choi, S. Li, W. Yu, L.J. Thompson, Appl. Phys. Lett. 78, 718 (2001)

    Article  ADS  Google Scholar 

  4. S.U.S. Choi, Z.G. Zhang, W. Yu, F.E. Lockwood, E.A. Grulke, Appl. Phys. Lett. 79, 2252 (2001)

    Article  ADS  Google Scholar 

  5. P. Keblinski, S.R. Phillpot, S.U.S. Choi, J.A. Eastman, Int. J. Heat Mass Transf. 45, 855 (2002)

    Article  MATH  Google Scholar 

  6. A. Gupta, R. Kumar, Appl. Phys. Lett. 91, 223102 (2007)

    Article  ADS  Google Scholar 

  7. P. Bhattacharya, S.K. Saha, A. Yadav, P.E. Phelan, R.S. Prasher, J. Appl. Phys. 95, 6492 (2004)

    Article  ADS  Google Scholar 

  8. R. Prasher, P. Bhattacharya, P.E. Phelan, Phys. Rev. Lett. 94, 025901 (2005)

    Article  ADS  Google Scholar 

  9. W. Evans, Appl. Phys. Lett. 88, 093116 (2006)

    Article  ADS  Google Scholar 

  10. J. Eapen, J. Li, S. Yip, Phys. Rev. Lett. 98, 028302 (2007)

    Article  ADS  Google Scholar 

  11. C.J. Yu, A.G. Richter, J. Kmetko, S.W. Dugan, A. Datta, P. Dutta, Phys. Rev. E, Stat. Nonlinear Soft Matter Phys. 63, 021205 (2001)

    Article  ADS  Google Scholar 

  12. K.C. Leong, C. Yang, S.M.S. Murshed, J. Nanopart. Res. 8, 245 (2006)

    Article  Google Scholar 

  13. W. Yu, S.U.S. Choi, J. Nanopart. Res. 5, 167 (2003)

    Article  Google Scholar 

  14. H.U. Kang, S.H. Kim, J.M. Oh, Exp. Heat Transf. 19, 181 (2006)

    Article  ADS  Google Scholar 

  15. O.M. Wilson, X.Y. Hu, D.G. Cahill, P.V. Braun, Phys. Rev. B, Condens. Matter Mater. Phys. 66, 224301 (2002)

    Article  ADS  Google Scholar 

  16. C. Nie, W.H. Marlow, Y.A. Hassan, Int. J. Heat Mass Transf. 51, 1342 (2008)

    Article  MATH  Google Scholar 

  17. S.M.S. Murshed, K.C. Leong, C. Yang, Int. J. Therm. Sci. 44, 367 (2005)

    Article  Google Scholar 

  18. H.T. Zhu, C.Y. Zhang, S.Q. Liu, Y.M. Tang, Y.S. Yin, Appl. Phys. Lett. 89, 023123 (2006)

    Article  ADS  Google Scholar 

  19. S. Sarkar, R.P. Selvam, J. Appl. Phys. 102, 074302 (2007)

    Article  ADS  Google Scholar 

  20. L. Li, Y.W. Zhang, H.B. Ma, M. Yang, J. Nanopart. Res. 12, 811 (2009)

    Article  Google Scholar 

  21. M.S. Daw, M.I. Baskes, Phys. Rev. B, Condens. Matter Mater. Phys. 29, 6443 (1984)

    Article  ADS  Google Scholar 

  22. D.A. McQuarrie, Statistical Mechanics (University Science Books, Sausalito, 2000)

    MATH  Google Scholar 

  23. C. Hoheisel, Theoretical Treatment of Liquids and Liquid Mixtures (Elsevier, Amsterdam, 1993)

    Google Scholar 

  24. R. Vogelsang, C. Hoheisel, J. Chem. Phys. 86, 6371 (1987)

    Article  ADS  Google Scholar 

  25. A.J.H. McGaughey, M. Kaviany, Int. J. Heat Mass Transf. 47, 1783 (2004)

    Article  MATH  Google Scholar 

  26. Z.M. Zhang, Nano/Microscale Heat Transfer (McGraw-Hill, New York, 2007)

    Google Scholar 

  27. J.C. Maxwell, Electricity and Magnetism (Clarendon, Oxford, 1873)

    Google Scholar 

  28. M. Chopkar, P.K. Das, I. Manna, Scr. Mater. 55, 549 (2006)

    Article  Google Scholar 

  29. M.P. Beck, Y.H. Yuan, P. Warrier, A.S. Teja, J. Nanopart. Res. 11, 1129 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuwen Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kang, H., Zhang, Y. & Yang, M. Molecular dynamics simulation of thermal conductivity of Cu–Ar nanofluid using EAM potential for Cu–Cu interactions. Appl. Phys. A 103, 1001–1008 (2011). https://doi.org/10.1007/s00339-011-6379-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00339-011-6379-z

Keywords

Navigation