Computational Software: Polymer Chain Generation for Coarse-Grained Models Using Radical-Like Polymerization

Authors

  • Morgane Mahaud
  • Zengqiang Zhai
  • Michel Perez
  • Olivier Lame
  • Claudio Fusco
  • Laurent Chazeau
  • Ali Makke
  • Grégory Marque
  • Julien Morthomas

DOI:

https://doi.org/10.4208/cicp.OA-2017-0146

Keywords:

Molecular dynamics (MD), coarse grained polymer model, LAMMPS, polymer, parallel computing.

Abstract

This paper presents major improvements in the efficiency of the so-called Radical-Like Polymerization (RLP) algorithm proposed in "Polymer chain generation for coarse-grained models using radical-like polymerization" [J. Chem. Phys. 128(2008)]. Three enhancements are detailed in this paper: (1) the capture radius of a radical is enlarged to increase the probability of finding a neighboring monomer; (2) between each growth step, equilibration is now performed with increasing the relaxation time depending on the actual chain size; (3) the RLP algorithm is now fully parallelized and proposed as a "fix" within the "Lammps" molecular dynamics simulation suite.

Published

2018-09-17

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How to Cite

Computational Software: Polymer Chain Generation for Coarse-Grained Models Using Radical-Like Polymerization. (2018). Communications in Computational Physics, 24(3), 885-898. https://doi.org/10.4208/cicp.OA-2017-0146