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Computational investigation of new separation schemes for branched polymers Yongmei Wang, Department of Chemistry, University of Memphis Separation and characterization of branched polymers according to its architecture is a real need and a real challenge. The simplest and first-implemented chromatographic techniques separate polymers according to size, which is the basis of size exclusion chromatography (i.e. SEC). The desire to separate polymers according to properties other than size has led to the advent of novel chromatographic methods such as liquid chromatography at the critical condition (LCCC) and liquid adsorption chromatography (LAC). However, the partitioning rules of star-shaped polymers in these chromatography conditions are not well understood. We perform Monte Carol simulations to investigate the partitioning rules of star polymers at all three chromatographic conditions and we contrast behavior between random walk (RW) model versus self-avoiding walks (SAW) model of polymer chains. The former is widely used to interpret experimental results, but the latter is a more accurate model of real star polymers encountered in experiments. Random walk stars in LAC mode f=2; D=14 f=2; D=29 f=3; D=14 f=3; D=29 f=4; D=14 f=4; D=29 f=6; D=14 f=6; D=29 f=8; D=14 f=8; D=29 50 ln(K) 40 30 20 10 0 100 200 300 Ntot 400 500 30 25 ln(K) 60 SAW stars in LAC mode 20 15 10 5 f=2; D=14 f=2; D=29 f=3; D=14 f=3; D=29 f=4; D=14 f=4; D=29 f=6; D=14 f=6; D=29 f=8; D=14 f=8; D=29 -100 0 100 Ntot 200 300 Two graphs on the left illustrate how the two models lead to different predictions. RW model predicts that in LAC model, partitioning coefficient K is independent of number of arms, only on total molecular weight Ntot; SAW model shows there are dependence on parameters other than Ntot.