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Atomistic Simulation Study of Controlled Nanostructure Patterning

Published online by Cambridge University Press:  10 February 2011

Byeongchan Lee
Affiliation:
Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
Kyeongjae Cho
Affiliation:
Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
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Abstract

We investigate the surface kinetics of Pt using the extended embedded-atom method, an extension of the embedded-atom method with additional degrees of freedom to include the nonbulk data from lower-coordinated systems as well as the bulk properties. The surface energies of the clean Pt (111) and Pt (100) surfaces are found to be 0.13 eV and 0.147 eV respectively, in excellent agreement with experiment. The Pt on Pt (111) adatom diffusion barrier is found to be 0.38 eV and predicted to be strongly strain-dependent, indicating that, in the compressive domain, adatoms are unstable and the diffusion barrier is lower; the nucleation occurs in the tensile domain. In addition, the dissociation barrier from the dimer configuration is found to be 0.82 eV. Therefore, we expect that atoms, once coalesced, are unlikely to dissociate into single adatoms. This essentially tells that by changing the applied strain, we can control the patterning of nanostructures on the metal surface.

Type
Research Article
Copyright
Copyright © Materials Research Society 2003

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References

1. Shchukin, V.A. and Bimberg, D., Rev. Mod. Phys. 71, 1125 (1999).Google Scholar
2. Binns, C., Surf. Sci. Reports 44, 1 (2001).Google Scholar
3. Larsson, M.I., Lee, B., Sabirynov, R., Cho, K., Nix, W., and Clemens, B.M. in Modeling and Numerical Simulation of Materials Behavior and Evolution, edited by Tikare, V., Olevsky, E.A., and Zavaliangos, A., (Mater. Res. Soc. Proc. 731, Pittsburgh, PA, 2002) W.3.14Google Scholar
4. Ratsch, C., Seitsonen, A. P., andScheffler, M., Phys. Rev. B 55, 6750 (1997).Google Scholar
5. Cai, J. and Ye, Y.Y., Phys. Rev. B 54, 8398 (1996).Google Scholar
6. Rose, J. H., Smith, J. R., Guinea, F., and Ferrante, J., Phys. Rev. B 29, 2963 (1984).Google Scholar
7. Banerjea, A. and Smith, J. R., Phys. Rev. B 37, 6632 (1988).Google Scholar
8. Bott, M., Hohage, M., Morgenstern, M., Michely, T., and Comsa, G., Phys. Rev. Lett. 76, 1304 (1996).Google Scholar
9. Feibelman, P. J., Phys. Rev. B. 81, 168 (1998).Google Scholar
10. Lee, B. and Cho, K. (in preparation).Google Scholar
11. Boisvert, G., Lewis, L. J., and Scheffler, M., Phys. Rev. B. 57, 1881 (1998).Google Scholar
12. Skriver, H. L. andRosengaard, N.M., Phys. Rev. B 46, 7157 (1992).Google Scholar
13. Metal Reference Book, 5th ed., edited by Smith, C. J. (Butter-worths, London, 1976), p. 186.Google Scholar
14. Boer, F. R. de, Boom, R., Mattens, W. C. M., Miedema, A. R., and Niessen, A. K., Cohesion in Metals (North-Holland, Amsterdam, 1988).Google Scholar
15. Kresse, G. and Hafner, J., Phys. Rev. B 47, 558 (1993).Google Scholar
16. Kresse, G. and Furthmüller, J., Comput. Mat. Sci. 6, 15 (1996).Google Scholar
17. Kresse, G. and Furthmüller, J., Phys. Rev. B 54, 11169 (1996).Google Scholar
18. Boisvert, G. and Lewis, L. J., Phys. Rev. B 59, 9846 (1999).Google Scholar