Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-25T15:45:36.679Z Has data issue: false hasContentIssue false

Computational Models for Multicomponent Diffusion in Polymeric Materials

Published online by Cambridge University Press:  10 February 2011

G. Rossi
Affiliation:
Ford Research Laboratory, Ford Motor Company, P.O. Box 2053, Mail Drop 3083, Dearborn, MI 48121–2053.
M. A. Samus
Affiliation:
Ford Research Laboratory, Ford Motor Company, P.O. Box 2053, Mail Drop 3083, Dearborn, MI 48121–2053.
Get access

Abstract

Situations where a polymeric material is exposed to a solvent mixture so that the different components within the mixture can diffuse into the polymer are common both in industrial applications and in biological processes. Often one of the components is taken up preferentially and its presence affects the diffusion properties of the remaining components. The problem of accounting for processes of this type has not been dealt with in a systematic way. This may in part be due to the difficulty of characterizing experimentally the separate diffusion behavior of the various components: data of this kind are now becoming available for simple binary mixtures. In order to model this class of problems, a lattice model involving a polymer matrix (M) and two diffusing components (A and B) has been introduced. The Monte Carlo evolution of the system has been examined for different values of the local A–M, B–M and A–B interactions. These results shed light on the microscopic origin of selective uptake.

Type
Research Article
Copyright
Copyright © Materials Research Society 1997

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. For a recent review see Rossi, G., Polym. Trends 4, 337 (1996).Google Scholar
2. Samus, M. A. and Rossi, G., in Multi-Dimensional Spectroscopy of Polymers, edited by Urban, M. W. and Provder, T. (ACS Symposium Series 598, 1995), p. 535.Google Scholar
3. Romanelli, J.F., Mayer, J.W., Kramer, E.J. and Russell, T.P., J. Polym. Sci.: Polym. Phys. Ed. 24, 263 (1986).Google Scholar
4. Rana, M.A. and Koenig, J.L., Macromolecules 27, 3727 (1994).Google Scholar
5. Demorest, R.L., J. Plast. Film Sheeting 8, 109 (1992);Google Scholar
Kollen, W.J. and Murthy, P.L., Annu. Tech. Conf. - Soc. Plast. Eng. 1, 1108 (1992).Google Scholar
6. Rossi, G. and Mazich, K.A., Phys. Rev. E48, 1182 (1993).Google Scholar
7. Samus, M.A. and Rossi, G., Macromolecules 29, 2275 (1996).Google Scholar
8. Rossi, G., Pincus, P. and de Gennes, P-G., Europhys. Lett. 32, 391 (1995).Google Scholar
9. Friedman, A. and Rossi, G., Macromolecules in press.Google Scholar
10. Theodorou, D.N., in Diffusion in Polymers edited by Neogi, P. (Marcel Dekker, 1996), p. 67.Google Scholar
11. Bortz, A.B., Kalos, M.H., Lebowitz, J.L. and Zendejas, M.A., Phys. Rev. B10, 535 (1974).Google Scholar
12. Marro, J., Lebowitz, J.L. and Kalos, M.H., Phys. Rev. Lett. 43, 282 (1979).Google Scholar
13. Alexander, F.J., Laberge, C.A., Lebowitz, J.L. and Zia, R.K.P., J. Stat. Phys. 82, 1133 (1996).Google Scholar
14. Colvin, R. and Moore, S., Modern Plastics, October 1996, p. 67.Google Scholar
15. Note that these properties are, at least in principle, calculable using the type of molecular level computer simulations described in ref. [10].Google Scholar