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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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01 Jan 2009
TL;DR: In these notes I discuss Monte Carlo simulations for the study of classical models in statistical mechanics and include a simple and direct proof that the method converges to the Boltzmann distribution.
Abstract: In these notes I discuss Monte Carlo simulations for the study of classical models in statistical mechanics. I include a simple and direct proof that the method converges to the Boltzmann distribution. Usually, physics articles discuss this important point by just giving a reference to the mathematical literature on “Markov chains”, where the proof is rather abstract. In these notes I give a proof of convergence which is self contained and uses only elementary algebra. In statistical mechanics one computes averages of a quantity A from the Boltzmann distribution, i.e. 〈A〉 = ∑

183 citations

Journal ArticleDOI
TL;DR: It was found that Fickian drug release from cylindrical matrices can be approximated nicely with the Weibull function, and this model has the benefit of providing a simple physical connection between the model parameters and the system geometry, which was something missing from other semiempirical models.
Abstract: Purpose. To verify the Higuchi law and study the drug release from cylindrical and spherical matrices by means of Monte Carlo computer simulation.

183 citations

Journal ArticleDOI
TL;DR: A new open system Monte Carlo procedure designed to overcome difficulties with insertion and deletion of molecules is introduced, and is shown to yield correct results for the volumetric properties of the Lennard-Jones fluid and water as well as the phase behavior of the CO2-ethanol binary system.
Abstract: A new open system Monte Carlo procedure designed to overcome difficulties with insertion and deletion of molecules is introduced. The method utilizes gradual insertions and deletions of molecules through the use of a continuous coupling parameter and an adaptive bias potential. The method draws upon concepts from previous open system molecular dynamics and expanded ensemble Monte Carlo techniques and is applied to both the grand canonical and osmotic ensembles. It is shown to yield correct results for the volumetric properties of the Lennard-Jones fluid and water as well as the phase behavior of the CO2-ethanol binary system.

183 citations

Journal ArticleDOI
TL;DR: In this article, a modified version of the standard SMC technique is proposed for smoothing in general state space models, which relies on forgetting properties of the filtering dynamics and the quality of the estimates produced.
Abstract: This paper concerns the use of sequential Monte Carlo methods (SMC) for smoothing in general state space models. A well-known problem when applying the standard SMC technique in the smoothing mode is that the resampling mechanism introduces degeneracy of the approximation in the path space. However, when performing maximum likelihood estimation via the EM algorithm, all functionals involved are of additive form for a large subclass of models. To cope with the problem in this case, a modification of the standard method (based on a technique proposed by Kitagawa and Sato) is suggested. Our algorithm relies on forgetting properties of the filtering dynamics and the quality of the estimates produced is investigated, both theoretically and via simulations.

183 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the phase transition of the restricted primitive model of ionic fluids and proposed a biased particle insertion/destruction scheme capable of sampling short interparticle distances.
Abstract: In this work, we investigate the liquid–vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four‐dimensional hypersphere and our own earlier Gibbs ensemble simulations with single‐ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T*c=0.053, ρ*c=0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids.

182 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202313
202242
20212
20203
20198
201853