Export citation

Export citation

Choose format for download:

Download Citation
  • Access by Xinjiang University

Spatially adaptive grand canonical ensemble Monte Carlo simulations

A. Chatterjee1, M. A. Katsoulakis2, and D. G. Vlachos1,*

  • 1Department of Chemical Engineering and Center for Catalytic Science and Technology, University of Delaware, Newark, Delaware 19716-3110, USA
  • 2Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-3110, USA

  • *Corresponding author.

Phys. Rev. E 71, 026702 – Published 9 February, 2005

DOI: https://doi.org/10.1103/PhysRevE.71.026702

Abstract

A spatially adaptive Monte Carlo method is introduced directly from the underlying microscopic mechanisms, which satisfies detailed balance, gives the correct noise, and describes accurately dynamic and equilibrium states for adsorption-desorption (grand canonical ensemble) processes. It enables simulations of large scales while capturing sharp gradients with molecular resolution at significantly reduced computational cost. A posteriori estimates, in the sense used in finite-elements methods, are developed for assessing errors (information loss) in coarse-graining and guiding mesh generation.

Article Text

References (26)

  1. K. Binder, Monte Carlo Methods in Statistical Physics (Springer-Verlag, Berlin, 1986), Vol. 7.
  2. D. P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics (Cambridge University Press, Cambridge, England, 2000).
  3. G. Ertl, Science 254, 1750 (1991).
  4. D. G. Vlachos Adv. Chem. Eng. ( to be published).
  5. T. P. Schulze, P. Smereka, and E. Weinan, J. Comput. Phys. 189, 197 (2003).
  6. S. Raimondeau and D. G. Vlachos, Chem. Eng. J. 90, 3 (2002).
  7. D. G. Vlachos, AIChE J. 43, 3031 (1997).
  8. R. Alkire and M. Verhoff, Electrochim. Acta 43, 2733 (1998).
  9. P. D. Christofides, AIChE J. 47, 514 (2001).
  10. R. Lam and D. G. Vlachos, Phys. Rev. B64, 035401 (2001).
  11. T. J. Pricer, M. J. Kushner, and R. C. Alkire, J. Electrochem. Soc. 149, C396 (2002).
  12. T. J. Pricer, M. J. Kushner, and R. C. Alkire, J. Electrochem. Soc. 149, C406 (2002).
  13. T. O. Drews, J. C. Ganley, and R. C. Alkire, J. Electrochem. Soc. 150, C325 (2003).
  14. T. P. Schulze, J. Cryst. Growth 263, 605 (2004).
  15. D. G. Vlachos, L. D. Schmidt, and R. Aris, J. Chem. Phys. 93, 8306 (1990).
  16. M. Tammaro, M. Sabella, and J. W. Evans, J. Chem. Phys. 103, 10277 (1995).
  17. C. W. Gear, J. Li, and I. G. Kevrekidis, Phys. Lett. A 316, 190 (2003).
  18. E. Weinan, B. Engquist, and Z. Y. Huang, Phys. Rev. B 67, 092101 (2003).
  19. M. Katsoulakis, A. J. Majda, and D. G. Vlachos, Proc. Natl. Acad. Sci. U.S.A. 100, 782 (2003).
  20. M. A. Katsoulakis, A. J. Majda, and D. G. Vlachos, J. Comput. Phys. 186, 250 (2003).
  21. M. A. Katsoulakis and D. G. Vlachos, J. Chem. Phys. 119, 9412 (2003).
  22. W. K. Burton, N. Cabrera, and F. C. Frank, Proc. R. Soc. London, Ser. A 243, 299 (1951).
  23. M. Bieterman and I. Babuska, Numer. Math. 40, 373 (1982).
  24. A. Ishikawa and T. Ogawa, Phys. Rev. E 65, 026131 (2002).
  25. T. L. Hill, An Introduction to Statistical Thermodynamics (Dover, New York, 1986).
  26. C. Johnson and A. Szepessy, Commun. Pure Appl. Math. 48, 199 (1995).

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation