Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites: data set

Abstract:
from [1]

Polymer nanocomposites are an important class of materials for engineering applications due to their high versatility and good mechanical properties combined with low density. By directly attaching the polymer chains to the nanofillers, the so-called grafting, a better load transfer between matrix and filler is achieved, and, in addition, a better dispersion of the fillers is obtained. Both result in enhanced mechanical properties. Since experimental investigations on the nanoscale are extremely challenging, complementary numerical studies are needed to unravel the mechanical behavior of polymer nanocomposites. To this end, molecular dynamics is ideally suited since it captures the microstructure, but is also numerically expensive. Therefore, this contribution presents a fast coarse-grained molecular dynamics model for the investigation of the mechanical behavior of grafted polymer nanocomposites. For this purpose, we extend an existing model by grafting bonds, which allows us to compare the effect of untreated and grafted fillers directly. In particular, we investigate the influence of filler content, grafting degree, and filler size on the stiffness and strength of the polymer (grafted) nanocomposites. We conclude that the grafting bonds have little effect on the stiffness, while the strength is significantly improved compared to the untreated fillers, which is in agreement with the literature. The presented molecular dynamics model for polymer grafted nanocomposites provides the basis for further investigations, particularly of the crucial matrix-filler interphase. In addition, this contribution translates molecular dynamics insights into mechanical properties, which bridges the gap to the engineering scale and thus represents a step towards exploiting the full potential of polymer (grafted) nanocomposites.

Contact:

Maximilian Ries
Institute of Applied Mechanics
Friedrich-Alexander-Universität Erlangen-Nürnberg
Egerlandstr. 5
91058 Erlangen

Software:

All MD simulations were performed with LAMMPS [2,3], version: 29 Oct 2020 / 20201029

Compiled with
Compiler: GNU C++ 4.8.5 20150623 (Red Hat 4.8.5-39) with OpenMP not enabled
C++ standard: C++11

Active compile time flags:
-DLAMMPS_GZIP
-DLAMMPS_SMALLBIG

Installed packages:
CLASS2, KSPACE, MANYBODY, MC, MOLECULE, MPIIO, OPT, VORONOI, USER-INTEL, USER-MISC, USER-MOLFILE, USER-NETCD

Polymer and polymer composite samples generated with self-avoiding random-walk algorithm [4]

Post-processing Matlab R2019b

License:

Creative Commons Attribution 4.0 International

Context:

Data set supplementing  journal paper:

[1] M. Ries, S. Reber, P. Steinmann, & S. Pfaller, “Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites,” Forces in Mechanics, vol. 12, p. 100 207, 2023.

Content:

structure of data set:

• 04_Equilibration
  folders containing the sample equilibration used in the presented parameter study
  • 01_filler_content
    variation of filler content
  • 02_grafting_density
    variation of grafting density
  • 03_grafting_potential
    variation of grafting potential
  • 04_filler_size
    variation of filler size
  • 05_reference
    reference samples without grafting
• 05_UT
  folders containing the uniaxial tension simulations used in the presented parameter study
  • 01_filler_content
    variation of filler content
  • 02_grafting_density
    variation of grafting density
  • 03_grafting_potential
    variation of grafting potential
  • 04_filler_size
    variation of filler size
  • 05_reference
    reference samples without grafting

Each simulation directory contains:

• lammps input file (*.in) of the specific simulation

• data file (*.data) containing the initial sample configuration

• input.prm: input parameters of the specific simulation (read by the input file)

• meta.info: meta data of the specific simulation run

• LAMMPS_out:
  simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below

  • thermo_out.Dat: raw output 

  • thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter)

  • thermo_out_STD.Dat: standard deviation of raw output

Output quantities (columns of *.Dat files):
Please note that the normalized Lennard-Jones unit set is used, so all quantities are normalized to fundamental mass, length, energy, time and the Boltzmann constant. Thus all entries are unitless [1].

• Step: time step 

• Time: time 

• TotEng: total energy 

• PotEng: potential energy

• KinEng: kinetic energy 

• E_pair: pair energy 

• E_bond: bond energy 

• E_angle: angle energy 

• E_dihed: dihedral energy 

• Temp: temperature

• Press: hydrostatic pressure

• Pxx: xx component of pressure tensor 

• Pyy: yy component of pressure tensor 

• Pzz: zz component of pressure tensor 

• Pxy: xy component of pressure tensor

• Pxz: xz component of pressure tensor

• Pyz: yz component of pressure tensor

• Volume: volume of simulation box 

• Lx: box length in x direction  

• Ly: box length in y direction  

• Lz: box length in z direction  

• Density: density  

• c_RG: radius of gyration scalar 

• c_RG[1]: squared radius of gyration tensor (xx component)  

• c_RG[2]: squared radius of gyration tensor (yy component)  

• c_RG[3]: squared radius of gyration tensor (zz component)  

• c_RG[4]: squared radius of gyration tensor (xy component)  

• c_RG[5]: squared radius of gyration tensor (xz component)  

• c_RG[6]: squared radius of gyration tensor (yz component)  

• c_bondave[1]: bond energy averaged over all atoms  

• c_bondave[2]: bond distance averaged over all atoms  

• c_bondave[3]: squared bond distance averaged over all atoms  

• c_angleave[1]: angle energy averaged over all atoms  

• c_angleave[2]: angle averaged over all atoms degree

• c_angleave[3]: cosine of angle 

• c_angleave[4]: squared cosine of angle 

• c_MSD[1]: mean squared displacement x-direction  

• c_MSD[2]: mean squared displacement y-direction  

• c_MSD[3]: mean squared displacement z-direction  

• c_MSD[4]: total mean squared displacement  

• c_COM[1]: x coordinate of center of mass  

• c_COM[2]: y coordinate of center of mass  

• c_COM[3]: z coordinate of center of mass  

• v_strain_xx: xx component of engineering strain tensor   

• v_strain_yy: yy component of engineering strain tensor    

• v_strain_zz: zz component of engineering strain tensor    

• v_vMisesequivstress: von Mises equivalent stress 

• v_Cauchy_xx: xx component of stress tensor  

• v_Cauchy_yy: yy component of stress tensor

• v_Cauchy_zz: zz component of stress tensor

• v_Cauchy_xy: xy component of stress tensor 

• v_Cauchy_xz: xz component of stress tensor 

• v_Cauchy_yz: yz component of stress tensor 

• v_strain_xy: xy component of engineering strain tensor   

• v_strain_xz: xz component of engineering strain tensor   

• v_strain_yz: yz component of engineering strain tensor   

References:

[1] M. Ries et al., “Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites,” Forces in Mechanics, vol. 12, p. 100 207, 2023.

[2] S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19.

[3] A. P. Thompson et al., “LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Computer Physics Communications, vol. 271, p. 108171, 2022.

[4] M. Ries, V. Dötschel, J. Seibert, S. Pfaller. “A self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites”, Zenodo, 2022. https://doi.org/10.5281/zenodo.6245699