2001
DOI: 10.1063/1.1337043
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Soft ellipsoid model for Gaussian polymer chains

Abstract: A soft ellipsoid model for Gaussian polymer chains is studied, following an idea proposed by Murat and Kremer [J. Chem. Phys. 108, 4340 (1998)]. In this model chain molecules are mapped onto ellipsoids with certain shapes, and to each shape a monomer density is assigned. In the first part of the work, the probabilities for the shapes and the associated monomer densities are studied in detail for Gaussian chains. Both quantities are expressed in terms of simple approximate formulae. The free energy of a system… Show more

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Cited by 56 publications
(67 citation statements)
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“…The close analogy between polymers and random walks has inspired many mathematical and statistical mechanical studies to analyze sizes and shapes of random walks [30][31][32][33][34][35][36][37][38][39][40][41][42][43]. Such studies validate Kuhn's insight and reveal broad distributions of radius of gyration and shape, as characterized by the eigenvalues of the gyration tensor.…”
Section: Introductionmentioning
confidence: 54%
“…The close analogy between polymers and random walks has inspired many mathematical and statistical mechanical studies to analyze sizes and shapes of random walks [30][31][32][33][34][35][36][37][38][39][40][41][42][43]. Such studies validate Kuhn's insight and reveal broad distributions of radius of gyration and shape, as characterized by the eigenvalues of the gyration tensor.…”
Section: Introductionmentioning
confidence: 54%
“…Since the results presented here challenge an important concept of polymer physics, they should hopefully be useful for a broad range of theoretical approaches which commonly assume the validity of the Gaussian chain model down to molecular scales [47,48,49]. This study shows that a polymer in dense solutions should not be viewed as one soft sphere (or ellipsoid) [50,51,52], but as a hierarchy of nested segmental correlation holes of all sizes aligned and correlated along the chain backbone ( Fig. 2 (b)).…”
Section: Discussionmentioning
confidence: 99%
“…One way to overcome this problem is through "multiscale modeling," where a set of simulations is performed at different levels of coarse-graining of the original system and in a subsequent step, information from different length scales is combined to provide the complete physical picture [7]. With such an approach, however, the challenge is not only to find the appropriate computational technique for each length scale simulated, but also to know (i ) the proper effective potential acting between coarse-grained units needed to carry out the simulations [8,9,10,11], and (ii ) the proper procedure for combining information from different scales of modeling once simulation data is acquired.…”
Section: Introductionmentioning
confidence: 99%