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      • Influence of molecular architecture on the entanglement network: topological analysis of linear, long- and short-chain branched polyethylene melts <i>via</i> Monte Carlo simulations

        Jeong, Seung Heum,Kim, Jun Mo,Yoon, Jeongha,Tzoumanekas, Christos,Krö,ger, Martin,Baig, Chunggi The Royal Society of Chemistry 2016 SOFT MATTER Vol.12 No.16

        <P>We present detailed results on the effect of chain branching on the topological properties of entangled polymer melts via an advanced connectivity-altering Monte Carlo (MC) algorithm. Eleven representative model linear, short-chain branched (SCB), and long-chain branched (LCB) polyethylene (PE) melts were employed, based on the total chain length and/or the longest linear chain dimension. Directly analyzing the entanglement [or the primitive path (PP)] network of the system via the Z-code, we quantified several important topological measures: (a) the PP contour length L-pp, (b) the number of entanglements Z(es) per chain, (c) the end-to-end length of an entanglement strand d(es), (d) the number of carbon atoms per entanglement strand N-es, and (e) the probability distribution for each of these quantities. The results show that the SCB polymer melts have significantly more compact overall chain conformations compared to the linear polymers, exhibiting, relative to the corresponding linear analogues, (a) similar to 20% smaller values of < L-pp > (the statistical average of L-pp), (b) similar to 30% smaller values of < Z(es)>, (c) similar to 20% larger values of < d(es)>, and (d) similar to 50% larger values of < N-es >. In contrast, despite the intrinsically smaller overall chain dimensions than those of the linear analogues, the LCB (H-shaped and A(3)AA(3) multiarm) PE melts exhibit relatively (a) 7-8% larger values of < L-pp >, (b) 6-11% larger values of < Z(es)> for the H-shaped melt and similar to 2% smaller values of < Z(es)> for the A(3)AA(3) multiarm, (c) 2-5% smaller values of < d(es)>, and (d) 7-11% smaller values of < N-es >. Several interesting features were also found in the results of the probability distribution functions P for each topological measure.</P>

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