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