Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-25T15:35:06.817Z Has data issue: false hasContentIssue false
  • English
  • Français

A Dynamic Monte Carlo Simulation of Sorbate Mobility in Zeolites: The Effects of Molecular Crowding on Sorbate Mobility

Published online by Cambridge University Press:  15 February 2011

Paul R. Van Tassel ,
Iwan Tantra ,
H. Ted Davis  and
Alon V. Mccormick
Paul R. Van Tassel
Affiliation:
University of Minnesota, Department of Chemical Engineering and Materials Science, 421 Washington Avenue SE, Minneapolis, MN 55455
Iwan Tantra
Affiliation:
University of Minnesota, Department of Chemical Engineering and Materials Science, 421 Washington Avenue SE, Minneapolis, MN 55455
H. Ted Davis
Affiliation:
University of Minnesota, Department of Chemical Engineering and Materials Science, 421 Washington Avenue SE, Minneapolis, MN 55455
Alon V. Mccormick
Affiliation:
University of Minnesota, Department of Chemical Engineering and Materials Science, 421 Washington Avenue SE, Minneapolis, MN 55455
Get access

Abstract

A finite lattice of adsorption sites, as shown by Monte Carlo simulation, is used to develop a simple hopping model of small molecules within the alpha cage of zeolite NaA. A two body attractive energetic interaction is employed for occupied pairs of nearest neighbor sites. A many body repulsive interaction term accounts for the crowding associated with site saturation. This term becomes important when the site-site spacing is less than the van der Waals diameter of the adsorbate. The dynamic Monte Carlo method is used to evaluate site to site hopping frequencies as a function of loading based on this potential energy function. As the sorbate-sorbate attractive interaction is increased (or, equivalently, as the temperature is reduced), mobility minima occur at certain lattice occupancies which may be explained by the formation of energetically favorable clusters on the cubocathedral lattice. In other words, molecular crowding can cause sorbate mobility to suffer minima as loading is increased. This prediction is in agreement with recent Xe NMR measurements.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 290: Symposium N – Dynamics in Small Confining Systems , 1992 , 147
Copyright
Copyright © Materials Research Society 1993

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. Soto, J. L. and Myers, A. L., Molec. Phys. 42, 971 (1981).Google Scholar
2. Kono, H. and Takasaka, A., J. Phys. Chem. 91, 4044 (1986).Google Scholar
3. Woods, G. B., Panagiotopoulos, A. Z., and Rowlinson, J. S., Molec. Phys. 63, 49 (1988).Google Scholar
4. Woods, G. B. and Rowlinson, J. S., J. Chem. Soc. Faraday Trans. 285, 765 (1989).Google Scholar
5. Razmus, D. M. and Hall, C. K., AIChE J. 37, 769 (1991).Google Scholar
6. Snurr, R. Q., June, R. L., Bell, A. T., and Theodorou, D. N., Molec. Simulation 8, 73 (1991).Google Scholar
7. Yashonath, S., Thomas, J.M., Nowak, A.K., and Cheetham, A.K., Nature 331, 601 (1988).Google Scholar
8. Leherte, L., Lie, G.C., Swamy, K.N., Clementi, E., Derouane, E.G., and Andre, J.M., Chem. Phys. Lett. 145, 237 (1988).Google Scholar
9. Yashonath, S., Demontis, P., and Klein, M., Chem. Phys. Lett. 153, 551 (1988).Google Scholar
10. Cohen De Lara, E., Kahn, R., and Goulay, A. M., J. Chem. Phys. 90, 7482 (1989).Google Scholar
11. Leherte, L., Andre, J. M., Vercauteran, D. P., and Derouane, E. G., J. Molec. Cat. 54, 426 (1989).Google Scholar
12. Demontis, P., Yashonath, S., and Klein, M., J. Phys. Chem. 93, 5016 (1989).Google Scholar
13. Fritzsche, S., Haberlandt, R., Kaerger, J., and Pfeifer, H., Chem. Phys. Let. 171, 109 (1990).Google Scholar
14. Pickett, S. D., Nowak, A. K., Thomas, J. M., Peterson, B. K., Swift, J. F. P., Cheetham, A. K., Ouden, C. J. J. den, Smit, B., and Post, M. F. M., J. Phys. Chem. 94, 1233 (1990).Google Scholar
15. June, R. L., Bell, A. T., and Theodorou, D. N., J. Phys. Chem. 94, 8232 (1990).Google Scholar
16. Yashonath, S., J. Phys. Chem. 95, 5877 (1991).Google Scholar
17. Yashonath, S., Demontis, P., and Klein, M., J. Phys. Chem. 95, 5881 (1991).Google Scholar
18. Van Tassel, P. R., Davis, H. T., and McCormick, A. V., Molec. Phys. 76, 411 (1992).Google Scholar
19. Tassel, P. R. Van, Davis, H. T., and McCormick, A. V., in preparation.Google Scholar
20. Kang, H. C. and Weinberg, W. H., J. Chem. Phys. 90, 2824 (1989).Google Scholar
21. Ruthven, D.M., Canad. J. Chem. 52, 3523 (1974).Google Scholar
22. Theodorou, D. and Wei, J., J. Cat. 83, 205 (1983).Google Scholar
23. Aust, E., Dahlke, K., and Emig, G., J. Cat. 115, 86 (1989).Google Scholar
24. Nelson, P.H., Kaiser, A.B., and Bibby, D.M., J. Cat. 127, 101 (1991).Google Scholar
25. Binder, K., Monte-Carlo Methods in Statistical Physics, Vol.7 of Topics in Current Physics, (Springer, Heidelberg, 1979).Google Scholar
26. Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., and Teller, E., J. Chem. Phys. 21, 1087 (1953).Google Scholar
27. Nivarthi, S.S. and McCormick, A.V., in preparation.Google Scholar