1998
DOI: 10.1002/(sici)1521-4044(199802)49:2/3<61::aid-apol61>3.0.co;2-v
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Simulation of polymer melts. I. Coarse-graining procedure for polycarbonates

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Cited by 464 publications
(615 citation statements)
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“…18 Tschöp et al suggested a spatial-coarse graining for polycarbonates, after which the chemical details are reintroduced into the coarse grained chains. 19 Quite successful in obtaining a well-equilibrated melt is the end-bridging Monte Carlo algorithm, as suggested by Pant and Theodorou, which, however, yields polydisperse melts because of the connectivity-altering moves. 20,3 Van der Vegt et al have investigated the influence of three different ways of generating initial configurations on the solubilities of small molecules in amorphous polymer melts.…”
Section: Simulation Model and Methodologymentioning
confidence: 99%
“…18 Tschöp et al suggested a spatial-coarse graining for polycarbonates, after which the chemical details are reintroduced into the coarse grained chains. 19 Quite successful in obtaining a well-equilibrated melt is the end-bridging Monte Carlo algorithm, as suggested by Pant and Theodorou, which, however, yields polydisperse melts because of the connectivity-altering moves. 20,3 Van der Vegt et al have investigated the influence of three different ways of generating initial configurations on the solubilities of small molecules in amorphous polymer melts.…”
Section: Simulation Model and Methodologymentioning
confidence: 99%
“…One first way to tackle this, was to reduce the number of de-grees of freedom by a systematic coarse-graining, which retains only those degrees of freedom that are relevant for the particular property of interest. Examples of molecular systems where the coarsegraining approach has been used with much success are fluids [9], lipid bilayers [10,11,12,13,14], and polymer systems [15,16,17,18].…”
Section: Introductionmentioning
confidence: 99%
“…Aside of this rigorous numerical analysis direction, entropy-based computational techniques were also developed and used for constructing approximations of coarse-grained (effective) potentials for models of large biomolecules and polymeric systems (fluids, melts). Optimal parametrization of effective potentials based on minimizing the relative entropy between equilibrium Gibbs states, e.g., 3,6,7 , extended previously developed inverse Monte Carlo methods, primarily based on force matching approaches, used in coarsegraining of macromolecules (see, e.g., 30,38 ). In 13 an extension to dynamics is proposed in the context of FokkerPlanck equations, by considering the corresponding relative entropy for discrete-time approximations of the transition probabilities.…”
Section: Introductionmentioning
confidence: 99%