Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica: dataset

Name: Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica: dataset
Creator: Zenodo
Published: 2022-08-08T10:11:08+08:00

Zenodo2022-08-08 更新2026-05-25 收录

数据链接：

https://zenodo.org/record/5557076 数据链接链接失效反馈

官方服务：

资源简介：

Abstract: (from [1]) The addition of fillers can significantly improve the mechanical behavior of polymers. The responsible mechanisms at the molecular level can be well assessed by particle-based simulation techniques, such as molecular dynamics. However, the high computational cost of these simulations prevents the study of macroscopic samples. Continuum-based approaches, particularly micromechanics, offer a more efficient alternative but require precise constitutive models for all constituents, which are usually unavailable at these small length scales. In this contribution, we derive a molecular-dynamics-informed constitutive law by employing a characterization strategy introduced in a previous publication. We choose silicon dioxide (silica) as an exemplary filler material used in polymer composites and perform uniaxial and shear deformation tests with molecular dynamics. The material exhibits elastoplastic behavior with a pronounced anisotropy. Based on the pseudo-experimental data, we calibrate an anisotropic elastic constitutive law and reproduce the material response for small strains accurately. The study validates the characterization strategy that facilitates the calibration of constitutive laws from molecular dynamics simulations. Furthermore, the obtained material model for coarse-grained silica forms the basis for future continuum-based investigations of polymer nanocomposites. In general, the presented transition from a fine-scale particle model to a coarse and computationally efficient continuum description adds to the body of knowledge of molecular science as well as the engineering community. Contact: Maximilian Ries Institute of Applied Mechanics Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 5 91058 Erlangen Software: All simulations were performed with LAMMPS [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 License: Creative Commons Attribution 4.0 International Context: Data set supplementing journal paper: [1] Ries, M.; Bauer, C.; Weber, F.; Steinmann, P. & Pfaller, S., "Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica", Mathematics and Mechanics of Solids, 2022, 108128652211080. This dataset contains the results presented in [1] and the necessary data to obtain those. Content: The files to reproduce our simulations and their results are structured as follows: 01_potentials tabulated potentials calibrated via iterative Boltzmann inversion in [2] kindly provided by the Müller-Plathe group at Technische Universität Darmstadt Angle_table angular interactions Bond_table bond interactions Nonbond_table pair interactions 02_sample Lammps data file (molecular style) of the investigated silica sample 03_simulations The condensed simulation directories with the naming convention given below are organized in the following subfolders: 01_time-proportional time-proportional simulation data 02_time-periodic time-periodic simulation data Each simulation directory contains: lammps input file (*.in) of the specific simulation 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 Naming convention: Silica-[deformation]-[direction]_[deformation function]-[deformation magnitude]_[deformation rate] ● [deformation]: uniaxial tension (UT), simple shear (SS) ● [direction]: deformation carried out in X/Y/Z (UT) or XY/XZ/YZ (SS) ● [deformation function]: time-proportional (strain), time-periodic (strain_ampl) ● [deformation magnitude]: maximum strain (time-proportional), strain amplitude (time-periodic); unitless ● [deformation rate]: rate-[strain rate] (only time-proportional): 0.001/ns-0.1/ns Output quantities (columns of *.Dat files): ● Step: time step ● Time: time in fs ● TotEng: total energy in kcal/mol ● PotEng: potential energy in kcal/mol ● KinEng: kinetic energy in kcal/mol ● E_pair: pair energy in kcal/mol ● E_bond: bond energy in kcal/mol ● E_angle: angle energy in kcal/mol ● E_dihed: dihedral energy in kcal/mol ● Temp: temperature in K ● Press: hydrostatic pressure in atm ● Pxx: xx component of pressure tensor in atm ● Pyy: yy component of pressure tensor in atm ● Pzz: zz component of pressure tensor in atm ● Pxy: xy component of pressure tensor in atm ● Pxz: xz component of pressure tensor in atm ● Pyz: yz component of pressure tensor in atm ● Volume: volume of simulation box in (Angstroms)^3 ● Lx: box length in x direction in Angstroms ● Ly: box length in y direction in Angstroms ● Lz: box length in z direction in Angstroms ● Density: density in g/(cm^3) ● c_RG: radius of gyration in Angstroms ● c_RG[1]: squared radius of gyration tensor (xx component) in (Angstroms)^2 ● c_RG[2]: squared radius of gyration tensor (yy component) in (Angstroms)^2 ● c_RG[3]: squared radius of gyration tensor (zz component) in (Angstroms)^2 ● c_RG[4]: squared radius of gyration tensor (xy component) in (Angstroms)^2 ● c_RG[5]: squared radius of gyration tensor (xz component) in (Angstroms)^2 ● c_RG[6]: squared radius of gyration tensor (yz component) in (Angstroms)^2 ● c_bondave[1]: bond energy averaged over all atoms in kcal/mol ● c_bondave[2]: bond distance averaged over all atoms in Angstroms ● c_bondave[3]: squared bond distance averaged over all atoms in (Angstroms)^2 ● c_angleave[1]: angle energy averaged over all atoms in kcal/mol ● c_angleave[2]: angle averaged over all atoms degree ● c_angleave[3]: cosine of angle (unitless) ● c_angleave[4]: squared cosine of angle (unitless) ● c_MSD[1]: mean squared displacement x-direction in (Angstroms)^2 ● c_MSD[2]: mean squared displacement y-direction in (Angstroms)^2 ● c_MSD[3]: mean squared displacement z-direction in (Angstroms)^2 ● c_MSD[4]: total mean squared displacement in (Angstroms)^2 ● c_COM[1]: x coordinate of center of mass in Angstroms ● c_COM[2]: y coordinate of center of mass in Angstroms ● c_COM[3]: z coordinate of center of mass in Angstroms ● v_strain_xx: xx component of engineering strain tensor (unitless) ● v_strain_yy: yy component of engineering strain tensor (unitless) ● v_strain_zz: zz component of engineering strain tensor (unitless) ● v_vMisesequivstress: von Mises equivalent stress in MPa ● v_Cauchy_xx: xx component of stress tensor in MPa ● v_Cauchy_yy: yy component of stress tensor in MPa ● v_Cauchy_zz: zz component of stress tensor in MPa ● v_Cauchy_xy: xy component of stress tensor in MPa ● v_Cauchy_xz: xz component of stress tensor in MPa ● v_Cauchy_yz: yz component of stress tensor in MPa ● v_strain_xy: xy component of engineering strain tensor (unitless) ● v_strain_xz: xz component of engineering strain tensor (unitless) ● v_strain_yz: yz component of engineering strain tensor (unitless) References: [1] Ries, M.; Bauer, C.; Weber, F.; Steinmann, P. & Pfaller, S., "Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica", Mathematics and Mechanics of Solids, 2022, 108128652211080. [2] Ghanbari, A.; Ndoro, T. V. M.; Leroy, F.; Rahimi, M.; Böhm, M. C. & Müller-Plathe, F., “Interphase Structure in Silica-Polystyrene Nanocomposites: A Coarse-Grained Molecular Dynamics Study”, Macromolecules, 2012, 45, 572-584. [3] Plimpton, S., “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19.

提供机构：

Zenodo

创建时间：

2022-08-08