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International Journal of Thermophysics

, Volume 26, Issue 1, pp 1–12 | Cite as

Transient Nonequilibrium Molecular Dynamic Simulations of Thermal Conductivity: 1. Simple Fluids

  • R. J. Hulse
  • R. L. Rowley
  • W. V. Wilding
Article

Abstract

Thermal conductivity has been previously obtained from molecular dynamics (MD) simulations using either equilibrium (EMD) simulations (from Green--Kubo equations) or from steady-state nonequilibrium (NEMD) simulations. In the case of NEMD, either boundary-driven steady states are simulated or constrained equations of motion are used to obtain steady-state heat transfer rates. Like their experimental counterparts, these nonequilibrium steady-state methods are time consuming and may have convection problems. Here we report a new transient method developed to provide accurate thermal conductivity predictions from MD simulations. In the proposed MD method, molecules that lie within a specified volume are instantaneously heated. The temperature decay of the system of molecules inside the heated volume is compared to the solution of the transient energy equation, and the thermal diffusivity is regressed. Since the density of the fluid is set in the simulation, only the isochoric heat capacity is needed in order to obtain the thermal conductivity. In this study the isochoric heat capacity is determined from energy fluctuations within the simulated fluid. The method is valid in the liquid, vapor, and critical regions. Simulated values for the thermal conductivity of a Lennard-Jones (LJ) fluid were obtained using this new method over a temperature range of 90 to 900 K and a density range of 1–35 kmol · m-3. These values compare favorably with experimental values for argon. The new method has a precision of ±10%. Compared to other methods, the algorithm is quick, easy to code, and applicable to small systems, making the simulations very efficient.

Keywords

Lennard-Jones fluid molecular dynamics nonequilibrium transient method thermal conductivity 

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References

  1. Heyes, D. M. 1994J. Phys.: Condens. Matter66409ADSGoogle Scholar
  2. Sharma, R. K., Tankeswar, K., Pathak, K. N. 1995J. Phys. Condens. Matter.7537ADSGoogle Scholar
  3. Vogelsang, R., Hoheisel, C., Ciccotti, G. 1987J. Chem. Phys.866371ADSGoogle Scholar
  4. Vogelsang, R., Hoheisel, G., Luckas, M. 1988Mol. Phys.641203ADSGoogle Scholar
  5. Muller-Plathe, F. 1997J. Chem. Phys.1066082ADSGoogle Scholar
  6. Ikeshoji, T., Hafskjold, B. 1994Mol. Phys.81251ADSGoogle Scholar
  7. Paolini, G. V., Ciccotti, G., Massobrio, C. 1986Phys. Rev. A.341355ADSGoogle Scholar
  8. Evans, D. J. 1982Phys. Lett. A.91457ADSGoogle Scholar
  9. Gillian, M. J. 1983J. Phys. C.16869ADSGoogle Scholar
  10. Heyes, D. M. 1984J. Chem. Soc. Faraday Trans.801363Google Scholar
  11. Bedrov, D., Smith, G. D. 2000J. Chem. Phys.1138080ADSGoogle Scholar
  12. Bird, R. B., Stewart, W. E., Lightfoot, E. N. 1960Transport PhenomenaJohn WileyNew YorkGoogle Scholar
  13. Poling, B. E., Prausnitz, J. M., O’Connell, J. P. 2001The Properties of Gases and LiquidsMcGraw-HillNew YorkGoogle Scholar
  14. Lawson, J., Erjavec, J. 2001Modern Statistics for Engineering and Quality ImprovementDuxburyPacific Grove, CAGoogle Scholar
  15. Hanley, H. J. M., McCarty, R. D., Haynes, W. M. 1974J. Phys. Chem. Ref. Data.3979CrossRefGoogle Scholar
  16. Michels, A., Sengers, J. V., De Klundert, L. J. M. 1963Physica29149CrossRefGoogle Scholar
  17. Le Neindre, B. 1972Int. J. Heat Mass Transfer151Google Scholar
  18. Hoheisel, C. 1990Comput. Phys. Rep.1229ADSGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of Chemical EngineeringBrigham Young UniversityProvoU.S.A.

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