Topic
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.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, Monte Carlo renormalization group methods were applied to the classical three-component Heisenberg model on a two-dimensional lattice and the expectation values of local correlations of spins and various sized block spins were computed using traditional Monte Carlo methods.
Abstract: Monte Carlo renormalization-group methods were applied to the classical three-component Heisenberg model on a two-dimensional lattice. Expectation values of local correlations of spins and various sized block spins were computed using traditional Monte Carlo methods. By matching quantities at different length scales generated by different Monte Carlo Hamiltonians we directly determined the renormalization of the nearest-neighbor coupling. Using these data and the results of high-temperature expansions and low-temperature renormalization-group calculations we have determined that this model does not have a phase transition. We have also obtained the amplitude for the low-temperature divergence of the susceptibility and the correlation length.
159 citations
TL;DR: A simulation protocol based on the reverse Monte Carlo method, which incorporates an energy constraint, is applied to model porous carbons in which hydrogen atoms are taken into account explicitly in addition to the carbon atoms and is found that the model reproduces the experimental pair correlation function with good accuracy.
Abstract: We apply a simulation protocol based on the reverse Monte Carlo (RMC) method, which incorporates an energy constraint, to model porous carbons. This method is called hybrid reverse Monte Carlo (HRMC), since it combines the features of the Monte Carlo and reverse Monte Carlo methods. The use of the energy constraint term helps alleviate the problem of the presence of unrealistic features (such as three- and four-membered carbon rings), reported in previous RMC studies of carbons, and also correctly describes the local environment of carbon atoms. The HRMC protocol is used to develop molecular models of saccharose-based porous carbons in which hydrogen atoms are taken into account explicitly in addition to the carbon atoms. We find that the model reproduces the experimental pair correlation function with good accuracy. The local structure differs from that obtained with a previous model (Pikunic, J.; Clinard, C.; Cohaut, N.; Gubbins, K. E.; Guet, J. M.; Pellenq, R. J.-M.; Rannou, I.; Rouzaud, J. N. Langmuir 2003, 19 (20), 8565). We study the local structure by calculating the nearest neighbor distribution, bond angle distribution, and ring statistics.
159 citations
TL;DR: In this article, it was shown that the recently developed configurational-bias Monte Carlo technique can be used in a grand canonical Monte Carlo simulation to make the insertion of chain molecules possible, and the use of this technique is illustrated by calculations of the adsorption isotherms of butane and hexane in the zeolite silicate.
Abstract: Simulations of open systems are performed conveniently in the grand canonical ensemble. For chain molecules simulations of this type converge very poorly because of the very low probability of a successful insertion in the exchange step. Here, it is shown that the recently developed configurational-bias Monte Carlo technique can be used in a grand canonical Monte Carlo simulation to make the insertion of chain molecules possible. The use of this technique is illustrated by calculations of the adsorption isotherms of butane and hexane in the zeolite silicate.
159 citations
TL;DR: In this paper, configurational-bias Monte Carlo sampling techniques have been developed which overcome the difficulties of sampling configuration space efficiently for all-atom molecular models and for branched species represented with united atom models.
Abstract: Configurational-bias Monte Carlo sampling techniques have been developed which overcome the difficulties of sampling configuration space efficiently for all-atom molecular models and for branched species represented with united atom models. Implementation details of this sampling scheme are discussed. The accuracy of a united atom forcefield with non-bond parameters optimized for zeolite adsorption and a widely used all-atom forcefield are evaluated by comparison with experimental sorption isotherms of linear and branched hydrocarbons.
159 citations
TL;DR: A class of numerical schemes of multi-level Monte Carlo Finite Volume (MLMC-FVM) type is presented for the approximation of random entropy solutions as well as of their k-point correlation functions and statistical moments of discontinuous solutions are found to be more regular than pathwise solutions.
Abstract: We consider scalar hyperbolic conservation laws in several (d ≥ 1) spatial dimensions with stochastic initial data. We prove existence and uniqueness of a random-entropy solution and show existence of statistical moments of any order k of this random entropy solution. We present a class of numerical schemes of multi-level Monte Carlo Finite Volume (MLMC-FVM) type for the approximation of random entropy solutions as well as of their k-point correlation functions. These schemes are shown to obey the same accuracy vs. work estimate as a single application of the finite volume solver for the corresponding deterministic problem. Numerical experiments demonstrating the efficiency of these schemes are presented. Statistical moments of discontinuous solutions are found to be more regular than pathwise solutions.
158 citations