Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-29T07:40:53.895Z Has data issue: false hasContentIssue false
  • English
  • Français

Monte Carlo Simulations of Copolymer Adsorption from Copolymer / Homopolymer Melts at Planar Chemically Patterned Surfaces

Published online by Cambridge University Press:  17 March 2011

James J. Semler  and
Jan Genzer
James J. Semler
Affiliation:
Department of Chemical Engineering, North Carolina State University, Raleigh, NC 27695-7905, U.S.A.
Jan Genzer
Affiliation:
Department of Chemical Engineering, North Carolina State University, Raleigh, NC 27695-7905, U.S.A.
Get access

Abstract

We investigate the adsorption of copolymers from copolymer / homopolymer mixtures at planar chemically patterned surfaces. The Monte Carlo bond fluctuation model is used in conjunction with configurational biased Monte Carlo moves to study the effect of: i) the copolymer microstructure, ii) the size and spatial distribution of chemical heterogeneities on the substrate, and iii) the polymer/substrate interactions on the ability of the copolymer to recognize the substrate chemical pattern. Our results confirm that the surface pattern recognition occurs whenever the characteristic size of the copolymer distribution sequence matches that of the surface heterogeneity domain. Moreover, the copolymer sequence distribution plays a crucial role in determining the extent of the surface pattern transfer into the bulk material. Our results reveal that more pronounced surface pattern transfer into the bulk occurs for small attractions of the adsorbing species to particular surface domains relative to the large attractions.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 710: Symposia DD – Polymer Interfaces and Thin Films , 2001 , DD8.5.1
Copyright
Copyright © Materials Research Society 2002

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

REFERENCES

1. Walheim, S., et al., Science, 283, 520 (1999).Google Scholar
2. Harrison, C., et al., Polymer, 30(13), 2733 (1998).Google Scholar
3. Muthukumar, M., Curr. Opin. Coll. Inter. Sci., 3, 48 (1998).Google Scholar
4. Fleer, G. J.; et al. Polymers at Interfaces, Chapman & Hall, London, 1993.Google Scholar
5. Sumithra, K. and Baumgaertner, A., J. Chem. Phys., 109(4), 1540 (1998).Google Scholar
6. Golumbfskie, A., et al., PNAS, 96(21), 11707 (1999).Google Scholar
7. Muthukumar, M., PNAS, 96(21), 11690 (1999).Google Scholar
8. Bratko, D., et al., Chem. Phys. Let., 280, 46 (1997).Google Scholar
9. Chakraborty, A., Phys. Rep., 342, 1 (2001); Chakraborty A. and Golumbfskie A., Ann. Rev. Phys. Chem., 52, 537 (2001).Google Scholar
10. Genzer, J., Phys. Rev. E 6302, 2601 (2001), J. Chem. Phys. 115, 4873 (2001); Adv. Colloid Interface Sci. 94, 105 (2001)Google Scholar
11. Frenkel, D. and Smit, B., Understanding Molecular Simulation: From Algorithms to Applications, Academic Press, San Deigo, 1996.Google Scholar
12. Binder, K., Monte Carlo and Molecular Dynamics Simulations in Polymer Science, Oxford University Press, New York, 1995.Google Scholar
13. Rosenbluth, M. and Rosenbluth, A., J. Chem. Phys., 23(2), 356, 1955.Google Scholar
14. Paul, W., et al., J. Phys. II (France), 1, 37 (1991).Google Scholar
15. Semler, J. and Genzer, J., unpublished results.Google Scholar