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Monte Carlo molecular modeling
About: Monte Carlo molecular modeling is a research topic. Over the lifetime, 11307 publications have been published within this topic receiving 409122 citations.
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138 citations
TL;DR: A deterministic high order accurate finite-difference WENO solver to the solution of the 1-D Boltzmann-Poisson system for semiconductor devices is developed and is a useful benchmark to check on the physical validity of various hydrodynamic and energy transport models.
138 citations
TL;DR: In this paper, the structure and thermodynamics of inhomogeneous polymer solutions in the framework of a coarse-grained off-lattice model were investigated, and properties of the liquid-vapor interface and the packing of the solution were investigated.
Abstract: We investigate the structure and thermodynamics of inhomogeneous polymer solutions in the framework of a coarse-grained off-lattice model. Properties of the liquidvapor interface and the packing of...
138 citations
TL;DR: In this paper, a quantum Monte Carlo method for tensor and other spin interactions such as those that are commonly encountered in nuclear structure calculations is described. But the main ingredients are a Hubbard-Stratonovich transformation to uncouple the spin degrees of freedom along with a fixed node approximation to maintain stability.
137 citations
TL;DR: In this paper, the authors used a standard Monte Carlo algorithm to study the slow dynamics of a binary Lennard-Jones glass-forming mixture at low temperature and found that the Monte Carlo approach is by far the most efficient way to simulate a stochastic dynamics since the relaxation is about 10 times faster than in Brownian dynamics and about 30 times faster in stochastically dynamic dynamics.
Abstract: We use a standard Monte Carlo algorithm to study the slow dynamics of a binary Lennard-Jones glass-forming mixture at low temperature. We find that the Monte Carlo approach is by far the most efficient way to simulate a stochastic dynamics since the relaxation is about 10 times faster than in Brownian dynamics and about 30 times faster than in stochastic dynamics. Moreover, the average dynamical behaviour of the system is in quantitative agreement with that obtained using Newtonian dynamics, apart from at very short times where thermal vibrations are suppressed. We show, however, that dynamic fluctuations quantified by four-point dynamic susceptibilities do retain a dependence on the microscopic dynamics, as recently predicted theoretically.
137 citations