In the preceding paper [A. E. Ismail, G. C. Rutledge, and G. Stephanopoulos J. Chem. Phys. (in press)] we introduced wavelet-accelerated Monte Carlo (WAMC), a coarse-graining methodology based on the wavelet transform, as a method for sampling polymer chains. In the present paper, we extend our analysis to consider excluded-volume effects by studying self-avoiding chains. We provide evidence that the coarse-grained potentials developed using the WAMC method obey phenomenological scaling laws, and use simple physical arguments for freely jointed chains to motivate these laws. We show that coarse-grained self-avoiding random walks can reproduce results obtained from simulations of the original, more-detailed chains to a high degree of accuracy, in orders of magnitude less time.
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15 June 2005
Research Article|
June 17 2005
Topological coarse graining of polymer chains using wavelet-accelerated Monte Carlo. II. Self-avoiding chains
Ahmed E. Ismail;
Ahmed E. Ismail
Department of Chemical Engineering,
Massachusetts Institute of Technology
, Cambridge, Massachusetts 02139
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George Stephanopoulos;
George Stephanopoulos
Department of Chemical Engineering,
Massachusetts Institute of Technology
, Cambridge, Massachusetts 02139
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Gregory C. Rutledge
Gregory C. Rutledge
a)
Department of Chemical Engineering,
Massachusetts Institute of Technology
, Cambridge, Massachusetts 02139
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a)
Electronic mail: rutledge@mit.edu
J. Chem. Phys. 122, 234902 (2005)
Article history
Received:
February 04 2005
Accepted:
March 31 2005
Connected Content
A companion article has been published:
Topological coarse graining of polymer chains using wavelet-accelerated Monte Carlo. I. Freely jointed chains
Citation
Ahmed E. Ismail, George Stephanopoulos, Gregory C. Rutledge; Topological coarse graining of polymer chains using wavelet-accelerated Monte Carlo. II. Self-avoiding chains. J. Chem. Phys. 15 June 2005; 122 (23): 234902. https://doi.org/10.1063/1.1924481
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