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Simulation of Graphene Elastomer Composites
Published in Titash Mondal, Anil K. Bhowmick, Graphene-Rubber Nanocomposites, 2023
Sumit Sharma, Pramod Rakt Patel
Thereafter, a crystal of 40 × 40 × 40 Å3 was created in which a Gr sheet of size 40 × 40 Å2 was placed centrally in the XY plane as shown in Figure 10.2a. The armchair and zig-zag edge of the Gr sheet were aligned along the X- and Y-axis respectively. The Gr sheet was formed with 680 atoms of carbon. Then, a Connolly surface was created at a distance of 1 Å, parallel to the plane of Gr on both sides of the Gr sheet to segregate different volumes in crystal, and then isosurface was created on it to avoid the packing of NR inside the Gr hexagonal rings as shown in Figure 10.2b. The estimation of energy was made with the COMPASS forcefield (Sun 1998). The 48 NR chain was packed inside this crystal with a density of 0.93 g cc−1 using an amorphous cell module. The packed crystal was composed of 7,016 atoms of Gr and NR which is shown in Figure 10.2c. The packed crystal was optimized for 5,000 iterations using the conjugate gradient method (Fletcher et al. 1964) with a convergence tolerance of 0.0001 kcal mol−1 for energy, 0.005 kcal mol−1 Å−1 for force, and 5 × 10−5 Å for displacement. The optimized geometry of the Gr-NR composite is shown in Figure 10.2d. Further, the system was equilibrated for 60 ps at room temperature and pressure, using an NPT ensemble with a time-step of 1 fs. The “Berendsen” thermostat (Berendsen et al. 1984) and barostat were used for temperature and pressure equilibration. After dynamics, a final density of 0.976 g cc−1 was achieved and shown in Figure 10.3.
Diffusion of rejuvenator in RAP binder observed at molecular scale
Published in Eyad Masad, Amit Bhasin, Tom Scarpas, Ilaria Menapace, Anupam Kumar, Advances in Materials and Pavement Performance Prediction, 2018
In this study, all molecular models were prepared by the Materials Studio package version 7.0, and all following MD simulations were performed by the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) (Plimpton 1995). The bonded and non-bonded potentials parameters were calculated using the Optimized Potentials for Liquid Simulations (OPLS) force field. This force field has been validated for predicting adsorptive properties for abroad range of substances, such as such as most common organics, small inorganic molecules, and polymers (Jorgensen et al. 1996). The time step of 1.0 fs was selected considering the balance between accuracy of simulation results and simulation time. A cut-off distance of 15.5 Å was used for van der Waals between molecules. As for the electrostatic interaction, Ewald summation method with a 6 Å cutoff distance was used. In all MD simulations, the Nosé-Hoover thermostat and Berendsen barostat were employed to control the temperature and pressure, respectively.
Numerical Simulation of Nanoparticle Formation
Published in Alexander V. Vakhrushev, Computational Multiscale Modeling of Multiphase Nanosystems, 2017
Usually, in real experiments, the molecular system exchanges energy with the environment. For calculating such power interactions, special algo- rithms—”thermostats” are used. Use of a thermostat allows one to carry out calculation of molecular dynamics at a constant temperature of the environment or to change it by a certain law. With this aim, the stage of condensation of an aerosol mix after active burning was considered. Therefore, the temperature of the system modeled was kept slightly above the normal one (at a level of 310 K) due to the use of a Berendsen thermostat (3.45a). As follows from this figure, with the Berendsen thermostat, the temperature was kept constant with an accuracy of 2–3%. Very important point of modeling is stabilization of the nanosystem pressure. Use of the “barostat” algorithms makes it possible to model the behavior of the system at constant pressure. The simplest of them is the Berendsen barostat in which the pressure is kept stationary by means of scaling the settlement cell. The positions of particles in systems are modified on each time step according to the factor of barostat scaling. The dependence of the change in the modeled volume of the system is presented in Figure 3.45b.
Molecular dynamics simulation of diffusion coefficients between different types of rejuvenator and aged asphalt binder
Published in International Journal of Pavement Engineering, 2020
All the molecular models were built through Materials Studio, and then transferred to Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) for the simulations (Plimpton 1995). The atomic trajectories were extracted and then viewed using Open Visualization Tool OVITO (Stukowski 2010). Temperature and pressure were controlled with the methods of Nose-Hoover thermostat and Anderson barostat. A cut-off distance of 15.5 Å was used for Van der Waals between molecules. The Optimized Potential for Liquid Simulations (OPLS-AA/M) force field (Robertson et al. 2015) was utilised to describe the bond and non-bond parameters, as shown in Equation (1).where, the four terms refer to bond stretches, angle bending, dihedral distortion, and non-covalent interactions, respectively. The force field parameters proposed by Li and Greenfield (2014a) were followed. In addition, for oxidised asphalt binder models, sulfoxides in the ring were simply treated as dimethyl sulfoxide (Liu et al. 1995) and all the ketones used the same force field parameter.
The compatibility of polylactic acid and polybutylene succinate blends by molecular and mesoscopic dynamics
Published in International Journal of Smart and Nano Materials, 2020
Cheng Lin, Liwu Liu, Yanju Liu, Jinsong Leng
For the packing systems, minimizations were performed by Smart Minimizer method to obtain the optimal structures. First, geometry optimization was conducted to lower the energy of the cells using Forcite module. Dynamics was carried out as follows: (i) an NVT ensemble simulation of 100ps at 500K; (ii) an NVT ensemble simulation of 800ps at 500K/1bar. Then the systems were equilibrated again at NPT condition at 298K/1bar for 500ps to obtain the optimal systems and prepare structures for next stage. The final step was an NVT at 298K for 100ps and the last 50ps was extracted for the data collections. It was worth mentioning that the basic principle of the dynamic process was to continue the simulation until the energy or temperature of the system was stable (see Section 3.1 for more details). In addition, the pressure and temperature were maintained through the Andersen barostat and the Berendsen thermostat. The van der Waals and Coulomb interaction forces were calculated by atom-based and Ewald summations, respectively. The cutoff distance was 12.5Å, the time step was 1fs, and trajectories were saved every 500 steps.
Modeling of fracture behavior in polymer composites using concurrent multi-scale coupling approach
Published in Mechanics of Advanced Materials and Structures, 2018
Shibo Li, Samit Roy, Vinu Unnikrishnan
In a typical MD simulation, deformations, if any, are applied on the atoms. Temperature and pressure are maintained at specified level using an appropriate thermostat and barostat, respectively. Using the formula given by Eq. (20), forces on each atom at any time are calculated as derivatives of the potential function. The interaction energy and forces are computed by the pairwise summation of the interaction between an atom and its neighbors. Lennard–Jones force field, which has a strongly repulsive core and weakly attractive tail, is used to simulate nonbonded the van der Waals interaction. Lennard–Jones interactions can be written as: where rij is the distance between the two nonbonded atoms, i and j, the potential well-depth parameter ϵ is considered to be the geometric mean of the values of the respective atom types, and the equilibrium spacing parameter σ determines the arithmetic mean of the individual parameters of the respective atom types.