Accurate method for the Brownian dynamics simulation of spherical particles with hard-body interactions

Journal of Chemical Physics

Volumn 117, Issue 20, 2002, Pages 9202-9214

  Barenbrug, Theo M A O M ^a   Peters, E A J F ^b   Schieber, Jay D ^c  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c Illinois Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ABSORPTION; BROWNIAN MOVEMENT; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; DIFFUSION; DISSOCIATION; PARTICLES (PARTICULATE MATTER); REACTION KINETICS;

BROWNIAN DYNAMICS SIMULATION; DIFFUSIVE MOTION; HARD BODY INTERACTIONS; NAIVE SIMULATION METHOD; SIMULATION ERROR;

MOLECULAR DYNAMICS;

EID: 0037159968     PISSN: 00219606     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.1515775     Document Type: Article

References (14)

1. H. C. Örtinger, Stochastic Processes in Polymeric Fluids (Springer, Berlin, 1996), p. 270. This work is based on the Ph.D. thesis of W. Strittmatter, "Numerische Behandlung von Stochastischen Dynamische Systemer," Univ. Freiburg, 1988.
2. K. Hyojoon and Joe S. Kook, Phys. Rev. E 61, 3426 (2000).
3. A. Einstein, Investigations on the Theory of the Brownian Movement, edited by R. Fürth (Dover, New York, 1956).
4. For elaborate comments on the applicability of this expression see also Ref. 3.
5. G. Lamm and K. Schulter, J. Chem. Phys. 78, 2713 (1983).
6. S. H. Northrup, S. A. Allison, and A. McCammon, J. Chem. Phys. 80, 1517 (1984).
7. S. H. Northrup, M. S. Curvin, S. A. Allison, and A. McCammon, J. Chem. Phys. 84, 2196 (1986).
8. G. Lamm, J. Chem. Phys. 80, 2845 (1984).
9. H. S. Carslaw and J. C. Jaeger, Conduction of Heat in Solids, 2nd ed. (Clarendon, Oxford, 1959), p. 382.
10. G. Arfken, Mathematical Methods for Physicists, 3rd ed. (Academic, New York, 1985), p. 647.
11. G. Arfken, Mathematical Methods for Physicists, 3rd ed. (Academic, New York, 1985), pp. 623-627.
12. The "Polar Marsaglia method" is more efficient than the "Box-Muller method" to obtain random numbers from a Gaussian distribution. P. E. Kloeden and E. Platen, Applications of Mathematics, Stochastic Modelling and Applied Probability (Springer, Berlin, 1992), Vol. 23, p. 13.
13. M. v. Smoluchowski, Z. Phys. Chem., Stoechiom. Verwandtschaftsl. 92, 129 (1917).
14. 1/2 = 4.14. This is far away from the converged value, 2.32, but gives k = 12.1 [see Eq. (24)], rather close to the von Smoluchowski limit of 12.6, to which the authors their result compared and which was obviously considered the "desired outcome."