Accurate measurements of the chemical potential of polymeric systems by Monte Carlo simulation
Nigel B. Wilding,Marcus Müller +1 more
TLDR
In this article, a new Monte Carlo method for estimating the chemical potential of model polymer systems is presented, based on the gradual insertion of a penetrable "ghost" polymer into the system and is effective for large chain lengths and at high densities.Abstract:
We present a new Monte Carlo method for estimating the chemical potential of model polymer systems. The method is based on the gradual insertion of a penetrable ‘‘ghost’’ polymer into the system and is effective for large chain lengths and at high densities. Insertion of the ghost chain is facilitated by use of an expanded ensemble, in which weighted transitions are permitted between states characterizing the strength of the excluded volume and thermal interactions experienced by the ghost chain. We discuss the implementation and optimization of the method within the framework of the bond fluctuation model and demonstrate its precision by a calculation of the finite‐size corrections to the chemical potential.read more
Citations
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Applications of Monte Carlo methods to statistical physics
TL;DR: An introductory review of the Monte Carlo method for the statistical mechanics of condensed matter systems is given in this paper, where basic principles (random number generation, simple sampling versus importance sampling, Markov chains and master equations) are explained and some classical applications (self-avoiding walks, percolation, the Ising model) are sketched.
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Extended ensemble monte carlo
TL;DR: A cross-disciplinary survey of a set of algorithms, which are now popular in a variety of fields in physics and statistical information processing, and stresses that an extension is not necessary restricted to the space of energy or temperature.
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Monte Carlo methods for phase equilibria of fluids
TL;DR: An overview of Monte Carlo methods for simulations of the phase behaviour of fluids can be found in this article, where the Gibbs ensemble method and histogram-reweighting Monte Carlo techniques are described in detail.
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Molecular and Mesoscale Simulation Methods for Polymer Materials
Sharon C. Glotzer,Wolfgang Paul +1 more
TL;DR: In this article, the authors provide an overview of some of the more popular simulation methods for modeling polymeric materials and their properties and behavior, as well as the structural properties that lead to them.
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Expanded grand canonical and Gibbs ensemble Monte Carlo simulation of polymers
TL;DR: In this article, a novel formalism for simulation of polymers in expanded grand canonical and expanded Gibbs ensembles is presented, where molecular creation and destruction attempts are replaced by transition attempts between states of a tagged chain of variable length.
References
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Bernd A. Berg,Thomas Neuhaus +1 more
TL;DR: A numerical simulation of the first-order phase transition in the 2D 10-state Potts model on lattices up to sizes 100 and a high-precision computation of the interfacial free energy per unit area is reported.
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The bond fluctuation method: a new effective algorithm for the dynamics of polymers in all spatial dimensions
I. Carmesin,Kurt Kremer +1 more
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New approach to Monte Carlo calculation of the free energy: Method of expanded ensembles
TL;DR: In this paper, the authors proposed a new effective Monte Carlo (MC) procedure for direct calculation of the free energy in a single MC run, where the partition function of the expanded ensemble is introduced including a sum of canonical partition functions with a set of temperatures and additive factors.
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Interdiffusion and self‐diffusion in polymer mixtures: A Monte Carlo study
Hans-Peter Deutsch,Kurt Binder +1 more
TL;DR: In this article, a lattice model for dense polymer solutions and polymer mixtures in three dimensions is presented, aiming to develop a model suitable for efficient computer simulation on vector processors, with a qualitatively realistic local dynamics.