Polymerization in Molecular Dynamics for LAMMPS and ESPResSo++

Copyright © 2014-2015 Pierre de Buyl

cg_md_polymerization is a repository containing reproducible computations for Molecular Dynamics simulations of coarse-grained particles that undergo a polymerization process. Chain growth and step growth are demonstrated.

This code is written by Pierre de Buyl and is released under the modified BSD license that can be found in the file LICENSE.

The appropriate citation when using this algorithm is P. de Buyl and E. Nies, J. Chem. Phys. 142, 134102 (2015) doi:10.1063/1.4916313 arXiv:1409.7498. Version 1.0 of this code was used in the publication.

Requirements and usage

• lammps The additional fix bond/create/random is necessary. It is found at https://github.com/pdebuyl/lammps/tree/fbc_random/src/MC.
• ESPResSo++ version 1.9.
• Make
• HDF5
• Python with NumPy, matplotlib and h5py

To reproduce the computations, invoke the make command.

source /path/to/espressopp/ESPRC
make chain_lammps LMP="/path/to/lmp"
make chain_espp
make epoxy_lammps LMP="/path/to/lmp"
make epoxy_espp

The seeds that are needed in the simulations, for the random number generators, are generated from the /dev/urandom device of your computer.

Parameters can be given to the simulations:

• RATE is the intrisic reaction rate k.
• TH is the interval between executions of the polymerization algorithm.
• Depending on the type of simulation, further parameters are available (number of particles, functionality of crosslinkers, number of time steps, etc).

Content of the repository

The Python programs for ESPResSo++ are code/chain_run.py and code/epoxy_run.py and the input scripts for LAMMPS are code/in.chain and code/in.epoxy.

Basic analysis programs are given for the two types of simulations: code/analyse_chain.py and code/analyse_epoxy.py.

Contributors

Jakub Krajniak