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Register a new userMolecular dynamics simulations of the dipolar-induced formation of magnetic nanochains and nanorings
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Iron, cobalt and nickel nanoparticles, grown in the gas phase, are known to arrange in chains and bracelet-like rings due to the long-range dipolar interaction between the ferromagnetic (or super-paramagnetic) particles. We investigate the dynamics and thermodynamics of such magnetic dipolar nanoparticles for low densities using molecular dynamics simulations and analyze the influence of temperature and external magnetic fields on two- and three-dimensional systems. The obtained phase diagrams can be understood by using simple energetic arguments.
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The large surface density changes associated with the (100) noble metals surface hex-reconstruction suggest the use of non-particle conserving simulation methods. We present an example of a surface Grand Canonical Monte Carlo applied to the transformation of a square non reconstructed surface to the hexagonally covered low temperature stable Au(100). On the other hand, classical Molecular Dynamics allows to investigate microscopic details of the reconstruction dynamics, and we show, as an example, retraction of a step and its interplay with the surface reconstruction/deconstruction mechanism.
The magnetic properties of Li_{1-x}Ni_{1+x}O_2 compounds with x ranging between 0.02 and 0.2 are investigated. Magnetization and ac susceptibility measured at temperatures between 2 K and 300 K reveal a high sensitivity to x, the excess Nickel concentration. We introduce a percolation model describing the formation of Ni clusters and use an Ising model to simulate their magnetic properties. Numerical results, obtained by a Monte-Carlo technique, are compared to the experimental data. We show the existence of a critical concentration, x_c = 0.136, locating the Ni percolation threshold. The system is superparamagnetic for x<x_c, while it is ferrimagnetic for x>x_c. The 180 Ni-O-Ni inter-plane super-exchange coupling J_perp simeq -110K is confirmed to be the predominant magnetic interaction. From the low temperature behavior, we find a clear indication of a 90 Ni-O-Ni intra-plane antiferromagnetic interaction $J_parallel simeq -1.5K$ which implies magnetic frustration.
The melting and crystallization of Al50Ni50} are studied by means of molecular dynamics computer simulations, using a potential of the embedded atom type to model the interactions between the particles. Systems in a slab geometry are simulated where the B2 phase of AlNi in the middle of an elongated simulation box is separated by two planar interfaces from the liquid phase, thereby considering the (100) crystal orientation. By determining the temperature dependence of the interface velocity, an accurate estimate of the melting temperature is provided. The value k=0.0025 m/s/K for the kinetic growth coefficient is found. This value is about two orders of magnitude smaller than that found in recent simulation studies of one-component metals. The classical Wilson-Frenkel model is not able to describe the crystal growth kinetics on a quantitative level. We argue that this is due to the neglect of diffusion processes in the liquid-crystal interface.
Molecular dynamics simulations on tensile deformation of initially defect free single crystal copper nanowire oriented in <001>{100} has been carried out at 10 K under adiabatic and isothermal loading conditions. The tensile behaviour was characterized by sharp rise in stress in elastic regime followed by sudden drop at the point of dislocation nucleation. The important finding is that the variation in dislocation density is correlated with the observed stress-strain response. Several interesting micro- structural features were observed during tensile deformation such as slip, phase transformation and pentagonal structure in necking region affecting the plastic deformation behaviour of single crystal copper nanowire.
A novel Stochastic Event-Driven Molecular Dynamics (SEDMD) algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses Event-Driven Molecular Dynamics (EDMD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.
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