Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T09:39:28.975Z Has data issue: false hasContentIssue false
  • English
  • Français

The Role of the Diffusion Mechanism in Models of the Evolution of Microstructure During Phase Separation

Published online by Cambridge University Press:  10 February 2011

T.T. Rautialnen  and
A.P. Sutton
T.T. Rautialnen
Affiliation:
Department of Materials, University of Oxford, Parks Road, Oxford OX 1 3PH, U.K.
A.P. Sutton
Affiliation:
Department of Materials, University of Oxford, Parks Road, Oxford OX 1 3PH, U.K.
Get access

Abstract

We have studied phase separation and subsequent coarsening of the microstructure in a two-dimensional square lattice using a stochastic Monte Carlo model and a deterministic mean field model. The differences and similarities between these approaches are discussed. We have found that a realistic diffusion mechanism through a vacancy motion in Monte Carlo simulations is cruicial in producing different coarsening mechanisms over a range of temperatures. This cannot be captured by the mean field model, in which the transformation is governed by the minimization of a free energy functional.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 529: Symposia BB – Computational & Mathematical Models of Microstructural Evolution , 1998 , 65
Copyright
Copyright © Materials Research Society 1998

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 Lifshitz, I.M., Slyozov, V.V., J. Phys. Chem. Solids 19, 35 (1961).Google Scholar
2 Huse, D.A., Phys. Rev. B 34, 7845 (1986).Google Scholar
3 Binder, K., Stauffer, D., Phys. Rev. Lett. 33, 1006 (1974).Google Scholar
4 Gunton, J.D., Miguel, M. San, Sahni, P., in Phase Transitions and Critical Phenomena, ed. by Domb, C. and Lebowitz, J.H., (Academic, London, 1983), Vol. 8, pp. 269–466.Google Scholar
5 Wang, Y., Chen, L.Q., Khachaturyan, A.G., in Computer Simulation in Materials Science, ed. by Kirchner, H.O. et al. , (Kluwer, Netherlands, 1996), pp. 325–371.Google Scholar
6 Chen, L.Q., Khachaturyan, A.G., Acta Metall. Mater. 39, 2533 (1991).Google Scholar
7 Vaks, V.G., Beiden, S.V., Dobretsov, V. Yu., JETP Lett. 61, 68 (1995).Google Scholar
8 Dobretsov, V. Yu., Vaks, V.G., Martin, G., Phys. Rev. B 54, 3227 (1996).Google Scholar
9 Yaldram, K., Binder, K., Acta Metall. Mater. 39, 707 (1991).Google Scholar
10 Fratzl, P., Penrose, O., Phys. Rev. B 50, 3477 (1994).Google Scholar
11 Frontera, C., Vives, E., Castdin, T., Planes, A., Phys. Rev. B 53, 2886 (1996).Google Scholar
12 Amar, J.G., Sullivan, F.E., Mountain, R.D., Phys. Rev. B 37 196 (1988).Google Scholar
13 Fratzl, P., Penrose, O., Phys. Rev. B 55, R6101 (1997).Google Scholar
14 Khachaturyan, A.G., Theory of Structural Transformations in Solids (Wiley, New York, 1983).Google Scholar
15 Binder, K., Heerman, D.W., Monte Carlo Simulation in Statistical Physics, (Springer-Verlaag, Berlin, 1988).Google Scholar
16 Bortz, A.B., Kalos, M.H., Lebowitz, J.L., J. Comp. Phys. 17, 10 (1975).Google Scholar
17 Novotny, M.A., Computers in Physics 9, 46 (1995).Google Scholar
18 Young, W.M., Elcock, E.W., Proc. Phys. Soc. 89, 735 (1966).Google Scholar
19 Athbnes, M., Bellon, P., Martin, G., Phil. Mag. A 76, 565 (1997).Google Scholar
20 Rautiainen, T.T., Sutton, A.P., to be publishedGoogle Scholar