Macromolecular Theory and Simulations

Cover image for Vol. 23 Issue 7

August 2014

Volume 23, Issue 7

Pages 411–472

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    1. Top of page
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    3. Masthead
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      Cover Picture: Macromol. Theory Simul. 7∕2014 (page 411)

      Eric Neuhaus, Thomas Herrmann, Iakovos Vittorias, Dieter Lilge, Gerd Mannebach, Andrei Gonioukh and Markus Busch

      Article first published online: 25 AUG 2014 | DOI: 10.1002/mats.201470019

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      Cover: A novel hybrid simulation approach combines the deterministic and stochastic modeling of complex polymerization networks, for all types of polymerization reactions in ideal and non-ideal reactors. The fast deterministic simulation solves the heat and pressure balances and generates position-dependent event frequency profiles. The detailed stochastic simulation offers insight into the polymeric microstructure of each macromolecule. Further details can be found in the article by E. Neuhaus, T. Herrmann, I. Vittorias, D. Lilge, G. Mannebach, A. Gonioukh, and M. Busch* on page 415.

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    1. Masthead: Macromol. Theory Simul. 7∕2014 (page 412)

      Article first published online: 25 AUG 2014 | DOI: 10.1002/mats.201470020

  3. Contents

    1. Top of page
    2. Cover Picture
    3. Masthead
    4. Contents
    5. Full Papers
    1. Contents: Macromol. Theory Simul. 7∕2014 (pages 413–414)

      Article first published online: 25 AUG 2014 | DOI: 10.1002/mats.201470021

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    5. Full Papers
    1. Modeling the Polymeric Microstructure of LDPE in Tubular and Autoclave Reactors with a Coupled Deterministic and Stochastic Simulation Approach (pages 415–428)

      Eric Neuhaus, Thomas Herrmann, Iakovos Vittorias, Dieter Lilge, Gerd Mannebach, Andrei Gonioukh and Markus Busch

      Article first published online: 11 JUL 2014 | DOI: 10.1002/mats.201400014

      Thumbnail image of graphical abstract

      A novel hybrid simulation approach is developed, which combines the advantages of deterministic and stochastic modeling of complex polymerization networks. The algorithm is applied to high-pressure ethylene polymerization in industrial tubular and continuous autoclave reactors with peroxide initiation. But in general, the presented approach can be used for all types of polymerization reactions in ideal and non-ideal reactors of any kind.

    2. Modeling of Network Formation in the Atom Transfer Radical Co-Polymerization (ATRP) of Vinyl/Divinyl Monomers Using a Multifunctional Polymer Molecule Approach (pages 429–441)

      Julio César Hernández-Ortiz, Eduardo Vivaldo-Lima, Marc A. Dubé and Alexander Penlidis

      Article first published online: 17 APR 2014 | DOI: 10.1002/mats.201400015

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      Polymer network formation by ATRP of vinyl/divinyl monomers is adequately described using a multifunctional polymer molecule approach. The model is validated with experimental data for ATRP of MA/EGDA at 60 °C. The evolution of living and dormant radical distribution indices (LRDI and DRDI) shows the importance of using a multifunctional modeling approach.

    3. Blends of Two Diblock Copolymers with Opposite Phase Behaviors (pages 442–451)

      Junhan Cho

      Article first published online: 11 MAY 2014 | DOI: 10.1002/mats.201400016

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      Theoretical analysis is performed on the stability and equilibrium morphologies of blends of A-b-B copolymer exhibiting self-assembly upon heating and A-b-C copolymer exhibiting reverse assembly upon cooling. The A-b-B/A-b-C blends reveal all possible self-assembly behavior spanning from self-assembly upon heating to a closed loop, and then to self-assembly upon cooling. The loop-forming blend shows tremendously enhanced pressure sensitivity.

    4. Models for Self-Avoiding Polymer Chains on the Tetrahedral Lattice (pages 452–463)

      Johannes Dietschreit, Dennis J. Diestler and Ernst-Walter Knapp

      Article first published online: 2 JUN 2014 | DOI: 10.1002/mats.201400023

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      Atomistic self-avoiding tetrahedral-lattice based polymer models are introduced, featuring bond and torsion angles suitable for chemical polymer backbone architecture. The self-avoidance is generalized to mimic realistic non-bonded atom distances. Efficient Monte Carlo algorithms are developed to generate polymers of several hundred atoms.

    5. Inferring Comonomer Content Using Crystaf: Uncertainty Analysis (pages 464–472)

      Arsia Takeh and Sachin Shanbhag

      Article first published online: 9 JUL 2014 | DOI: 10.1002/mats.201400034

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      Uncertainty in the estimation of comonomer content (CCD) is characterized in random copolymers using Crystaf. We ask questions such as: (i) how often is the estimated CCD within a specified range of the true value? (ii) what is the variability in the inferred CCD? (iii) how does model parameterization affect the predictions?

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