@Article{CiCP-24-3,
author = {Morgane, Mahaud and Zhai, Zengqiang and Perez, Michel and Olivier, Lame and Fusco, Claudio and Laurent, Chazeau and Makke, Ali and Marque, Grégory and Morthomas, Julien},
title = {Computational Software: Polymer Chain Generation for Coarse-Grained Models Using Radical-Like Polymerization},
journal = {Communications in Computational Physics},
year = {2018},
volume = {24},
number = {3},
pages = {885--898},
abstract = {<p style="text-align: justify;">This paper presents major improvements in the efficiency of the so-called
Radical-Like Polymerization (RLP) algorithm proposed in &quot;Polymer chain generation
for coarse-grained models using radical-like polymerization&quot; [J. Chem. Phys. <strong>128</strong>(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 &quot;fix&quot; within the &quot;Lammps&quot; molecular dynamics simulation
suite.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.OA-2017-0146},
url = {https://global-sci.com/article/79974/computational-software-polymer-chain-generation-for-coarse-grained-models-using-radical-like-polymerization}
}