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Multiscale Modeling of Wave Propagation: FDTD/MD Hybrid Method

Published online by Cambridge University Press:  01 February 2011

Krishna Muralidharan
Affiliation:
Dept of Materials Science and Engineering, University of Arizona, Tucson, AZ 85712, U.S.A
Pierre A. Deymier
Affiliation:
Dept of Materials Science and Engineering, University of Arizona, Tucson, AZ 85712, U.S.A
Joseph H. Simmons
Affiliation:
Dept of Materials Science and Engineering, University of Arizona, Tucson, AZ 85712, U.S.A
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Abstract

Atomic level processes often play an important role in the way a material responds to an external field. Thus in order to model the behavior of materials accurately, it is necessary to develop simulation techniques which can effectively couple atomistic effects to the macroscopic properties of the model system and vice-versa. In other words, a multiscale methodology needs to be developed to bridge the different length and time scales. In this work we study the propagation of an elastic wave through a coupled continuum-atomistic medium. The equations of motion for the wave propagation through the continuum are solved using the Finite Difference Time Domain Method (FDTD). Simultaneously we use Molecular Dynamics (MD) to examine the effect of the wave packet on the atomic dynamics and the effect of atomic dynamics on the propagation of the wave. The handshaking between the FDTD region and the MD region is concurrent.

Type
Research Article
Copyright
Copyright © Materials Research Society 2002

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References

1. Broughton, J.Q., Abraham, F.F., Bernstein, N., and Kaxiras, E., Phys. Rev. B. 60, 2391 (1999).Google Scholar
2. Abraham, F.F., Broughton, J.Q., Bernstein, N., and Kaxiras, E., Comp. Phys. 12, 538 (1998).Google Scholar
3. Rudd, R.E. and Broughton, J.Q., Phys. Rev. B 58, R5893 (1998).Google Scholar
4. Sigalas, M.M. and Garcia, N., J. Appl. Phys. 87, 32122 (2000).Google Scholar
5. Garcia-Pablos, D., Sigilas, M.M, Espinosa, F.R.M.de, Torres, M., Kafesaki, M., Garcia, N., Phys. Rev. Lett. 84, 4349 (2000).Google Scholar
6. Rapaport, D.C., “The Art of Molecular Dynamics Simulation,” (Cambridge University Press, Cambridge, 1995).Google Scholar
7. Parrinello, M. and Rahman, A., J. Appl. Phys. 52, 7182 (1981).Google Scholar
8. Press, W. H., Teulosky, S. A., Vetterling, W. T., and Flannery, B. P., “Numerical Recipes in Fortran, The Art of Scientific Computing Second Edition,” (Cambridge University Press, Cambridge, 1992), pp 501502.Google Scholar