Hostname: page-component-745bb68f8f-f46jp Total loading time: 0 Render date: 2025-01-12T07:59:11.011Z Has data issue: false hasContentIssue false
  • English
  • Français

Accelerating the Dynamics of Infrequent Events: Combining Hyperdynamics and Parallel Replica Dynamics to Treat Epitaxial Layer Growth

Published online by Cambridge University Press:  10 February 2011

A. F. Voter  and
T. C. Germann
A. F. Voter
Affiliation:
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545; {afv,tcg}@lanl.gov
T. C. Germann
Affiliation:
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545; {afv,tcg}@lanl.gov
Get access

Abstract

During the growth of a surface, morphology-controlling diffusion events occur over time scales that far exceed those accessible to molecular dynamics (MD) simulation. Kinetic Monte Carlo offers a way to reach much longer times, but suffers from the fact that the dynamics are correct only if all possible diffusion events are specified in advance. This is difficult due to the concerted nature of many of the recently discovered surface diffusion mechanisms and the complex configurations that arise during real growth. Here we describe two new approaches for this type of problem. The first, hyperdynamics, is an accelerated MD method, in which the trajectory is run on a modified potential energy surface and time is accumulated as a statistical property. Relative to regular MD, hyperdynamics can give computational gains of more than 102. The second method offers a way to parallelize the dynamics efficiently for systems too small for conventional parallel MD algorithms. Both methods exploit the infrequent-event nature of the diffusion process. After an introductory description of these methods, we present preliminary results from simulations combining the two approaches to reach near-millisecond time scales on systems relevant to epitaxial metal growth.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 528: Symposia AA – Mechanisms & Principals of Epitaxial Growth in Metallic Systems , 1998 , 221
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. Zhou, S.J., Preston, D.L., Lomdahl, P.S., and Beazley, D.M., Science 279, 1525 (1998).Google Scholar
2. Holian, B.L. and Lomdahl, P.S., Science, in press, 1998.Google Scholar
3. Karetta, F. and Urbassek, H.M., J. Appl. Phys. 71, 5410 (1992).Google Scholar
4. Lyndenbell, R.M., Surf. Sci. 259,129 (1991).Google Scholar
5. Chen, E.T., Barnett, R.N., and Landman, U., Phys. Rev. B 41,439 (1990).Google Scholar
6. Rubia, T.D. De La, Caro, A., and Spaczer, M., Phys. Rev. B 47, 11483 (1993).Google Scholar
7. Zhong, W., Cai, Y., and Tomanek, D., Nature 362,435 (1993).Google Scholar
8. Voter, A.F. and Doll, J.D., J. Chem. Phys. 80, 5832 (1984).Google Scholar
9. Voter, A.F. and Doll, J.D., J. Chem. Phys. 82, 80 (1985).Google Scholar
10. Voter, A.F., Phys. Rev. B 34, 6819 (1986).Google Scholar
11. Feibelman, P.J., Phys. Rev. Lett 65, 729 (1990).Google Scholar
12. Bassett, D.W. and Webber, P.R., Surf. Sci. 70, 520 (1978).Google Scholar
13. Halichioglu, T. and Pound, G.M., Thin Solid Films 57, 241 (1979).Google Scholar
14. Wrigley, J.D. and Ehrlich, G., Phys. Rev. Lett. 44, 661 (1980).Google Scholar
15. Tung, R.T. and Graham, W.R., Surf. Sci. 97, 73 (1980).Google Scholar
16. Kellogg, G.L. and Feibelman, P.J., Phys. Rev. Lett. 64, 3143 (1990).Google Scholar
17. Chen, C. and Tsong, T.T., Phys. Rev. Lett. 64, 3147 (1990).Google Scholar
18. Liu, C.L., Cohen, J.M., Adams, J.B., and Voter, A.F., Surf. Sci., 253, 334 (1991).Google Scholar
19. Hansen, L., Stoltze, P., Jacobsen, K.W., and Norskov, J.K., Phys. Rev. B 44, 6523 (1991).Google Scholar
20. Kellogg, G.L. and Voter, A.F., Phys. Rev. Lett. 67, 622 (1991).Google Scholar
21. Liu, C.L. and Adams, J.B., Surf. Sci. 268, 73 (1992).Google Scholar
22. Wang, R. and Fichthorn, K.A., Molec. Sim. 11, 105 (1993).Google Scholar
23. Villarba, M. and Jónsson, H., Phys. Rev. B 49, 2208 (1994).Google Scholar
24. Liu, S., Zhang, Z., Norskov, J., and Metiu, H., Surf. Sci. 321, 161 (1994).Google Scholar
25. Hamilton, J.C., Daw, M.S., and Foiles, S.M., Phys. Rev. Lett. 74, 2760 (1995).Google Scholar
26. Shi, Z-P., Zhang, Z., Swan, A.K., and Wendelken, J.F., Phys. Rev. Lett. 76, 4927 (1996).Google Scholar
27. Cohen, J.M., Surf. Sci. Lett. 306, L545 (1994).Google Scholar
28. Ehrlich, G. and Hudda, F.G., J. Chem. Phys. 44, 1039 (1966); R.L. Schwoebel, J. Appl. Phys. 40, 614 (1969).Google Scholar
29. Stoltze, P. and Norskov, J.K., Phys. Rev. B 48, 5607 (1993).Google Scholar
30. Egelhoff, W.F. Jr., and Jacob, I., Phys. Rev. Lett. 62, 921 (1989).Google Scholar
31. Voter, A.E, J. Chem. Phys. 106, 4665 (1997).Google Scholar
32. Voter, A.F., Phys. Rev. Lett. 78, 3908 (1997).Google Scholar
33. Voter, A.F., Phys. Rev. B, in press, 1998.Google Scholar
34. Marcelin, R., Ann. Physique 3, 120 (1915).Google Scholar
35. Eyring, H., J. Chem. Phys. 3, 107 (1935).Google Scholar
36. Wigner, E., Trans. Faraday Soc. 34, 29 (1938).Google Scholar
37. Anderson, J.B., Adv. Chem. Phys. 91, 381 (1995).Google Scholar
38. Bennett, C.H., in Algorithms for Chemical Computation, edited by Christofferson, R.E. (American Chemical Society, Washington, DC, 1977), p. 63.Google Scholar
39. Chandler, D., J. Chem. Phys. 68, 2959 (1978); J.A. Montgomery, Jr., D. Chandler, and B.J. Berne, J. Chem. Phys. 70, 4056 (1979).Google Scholar
40. Steiner, M. M., Genilloud, P.-A., and Wilkins, J. W., Phys. Rev. B 57, 10236 (1998).Google Scholar
41. Voter, A.F., Doll, J.D., and Cohen, J.M., J. Chem. Phys. 90, 2045 (1989).Google Scholar
42. Sevick, E.M., Bell, A.T., and Theodorou, D.N., J. Chem. Phys. 98, 3196 (1993).Google Scholar
43. Vineyard, G.H., J. Phys. Chem. Solids 3, 121 (1957).Google Scholar
44. Daw, M.S., Foiles, S.M., and Baskes, M.I., Mater. Sci. Reports 9, 251 (1993).Google Scholar