Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T18:37:20.849Z Has data issue: false hasContentIssue false
  • English
  • Français

Molecular Dynamic Computer Simulation of Thin Film's Heat Dissipation Rate

Published online by Cambridge University Press:  01 February 2011

Ya-Yun Cheng ,
Horng-Ming Hsieh  and
Cheng-Chung Lee
Ya-Yun Cheng
Affiliation:
[email protected], National Central University, Institute of optical science, No.300, Jhongda Rd., Chung-Li, N/A, 320, Taiwan
Horng-Ming Hsieh
Affiliation:
[email protected], Institute of Nuclear Energy Research, Lungtan, N/A, 325, Taiwan
Cheng-Chung Lee
Affiliation:
[email protected], National Central University, Institute of optical science, Chung-Li, 320, Taiwan
Get access

Abstract

Heat dissipation rate of the thin film is theoretically related to the thickness of the film. As the film grows on a substrate of constant temperature, the heat dissipation rate would be lower when the film becomes thicker. It is difficult to observe rate change during the film growth through experiment. With MD simulation, this rate can be "observed". A system including Platinum substrate at constant temperature 300K is setup. The constant temperature is obtained by Phantom method.

The average temperature of aluminum thin film is 600K. For various thickness of the film: 3.656nm, 5.302nm, and 7.567nm. The average temperature decays exponentially. Through the simple equation T=(T0-Ts)exp(-kt/d2PCp)+Ts, the dissipation rate should follow the parameter R=k/d2PCp and the parameter α=k/£Cp is the thermal diffusivity. It is observed that the thermal diffusivity increases with film thickness increases.

Keywords

thermal conductivityfilmsimulation
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 910: Symposium A – Amorphous and Polycrystalline Thin-Film Silicon Science and Technology – 2006 , 2006 , 0910-A05-03
Copyright
Copyright © Materials Research Society 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Abramson, A.R. and Tien., C.L. Microscale Thermophysical Engineering, Vol.3:pp.229–244.(1999)Google Scholar
2. Bruschi, P., Cagnoni, P. and Nannnini, A., Phys. Rev. B 55, pp.7955–7953(1997)Google Scholar
3. Helin., W, Zuli., L and Kailun., Y, Vacuum 52, 1999, pp.435–440(1999)Google Scholar
4. Harris, R., Phys. Rev. B 38, pp.9323–9326 (1988)Google Scholar
5. Maedae, A. and Munakata., T. Phys. Rev. E 52, pp.234–239 (1995)Google Scholar
6. Ibsen, J., Soto, R. and Cordero, P., Phys. Rev. E 52, pp.4533–4536(1995)Google Scholar
7. Daw, M. S. and M. Baskes, I., Phys. Rev B 29, pp.6443–6453(1984)Google Scholar
8. Wadley, H. N. G., Zhou, X. and Johnson, R. A., Mat. Res. Soc. Symp. Proc. 672,pp.04.1.1 (2001)Google Scholar
9. Kittel, , “Introduction to solid state physics”, chapter 1 (Wiley: Weinheim, New York, 2002).Google Scholar
10. Maruyama, S. Advances in Numerical Heat Transfer, Minkowycz, W. J. and E. M. vol. 2, Chap. 6, p189–226 (2000)Google Scholar
11. Allen, M. P. and Tildesley, D. J., “Computer Simulation of Liquids”, (Clarendon Press: Oxford, 1990, 1987)Google Scholar