اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدAn Event-Driven Hybrid Molecular Dynamics and Direct Simulation Monte Carlo Algorithm
131
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
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.
قيم البحث
اقرأ أيضاً
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 transform
ation 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 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.
We introduce a simple but efficient method for grand-canonical twist averaging in quantum Monte Carlo calculations. By evaluating the thermodynamic grand potential instead of the ground state total energy, we greatly reduce the sampling errors caused
by twist-dependent fluctuations in the particle number. We apply this method to the electron gas and to metallic lithium, aluminum, and solid atomic hydrogen. We show that, even when using a small number of twists, grand-canonical twist averaging of the grand potential produces better estimates of ground state energies than the widely used canonical twist-averaging approach.
UKQCDs dynamical fermion project uses the Generalised Hybrid Monte-Carlo (GHMC) algorithm to generate QCD gauge configurations for a non-perturbatively O(a) improved Wilson action with two degenerate sea-quark flavours. We describe our implementation
of the algorithm on the Cray-T3E, concentrating on issues arising from code verification and performance optimisation, such as parameter tuning, reversibility, the effect of precision, the choice of matrix inverter and the behaviour of different molecular dynamics integration schemes.
By carrying out Monte Carlo simulations based on the two-species atomic-scale kinetic growth model of GaAs(001) homoepitaxy and comparing the results with scanning tunneling microscope images, we show that initial growing islands undergo the structur
al transformation before adopting the proper beta2(2x4) reconstruction.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
