Configurational-bias Monte Carlo methods

Applications of the Configurational Bias Monte Carlo Method... 

Martin M G and J I Siepmann 1999. Novel Configurational-bias Monte Carlo Method for Blanche Molecules. Transferable Potentials for Phase Equilibria. 2. United-atom Description of Branchi Alkanes. Journal of Physical Chemistry 103 4508-4517. 

Conductivity electrical, 27 20, 21 active site, 27 216, 217 temperature dependence, 27 20, 21 tin-antimony oxide, 30 100, 109 tin(IV) oxide, 30 108-109 Configurational-bias Monte Carlo method (CB-MC)... 

Vendruscolo, M. Modified configurational bias Monte Carlo method for simulation of polymer systems. J. Chem. Phys. 1997, 106, 2970-6. 

Escobedo, F.A., De Pablo, J.J. Extended continuum configurational bias Monte Carlo methods for simulation of flexible molecules. J. Chem. Phys. 1995, 102, 2636-52. 

The configurational-bias Monte Carlo method (CB-MC) (112) was developed to overcome these sorts of problems. Instead of a random insertion into the zeolite host, the guest molecule is grown atom by atom within the host in a way that avoids unfavorable overlap with the zeolite atoms. 

The essence of the configurational bias Monte Carlo method is that a growing molecule is preferentially directed (i.e. biased) towards acceptable structures The effects of these biases can then be removed by modifying the acceptance rules The configurational bias methods are based upon work published in 1955 by Rosenbluth and Rosenbluth... 

Let us now consider how the configurational bias Monte Carlo method would deal with this problem. Again, the first site (S) is chosen at random. We next consider where to place the second unit. The sites adjacent to S are examined to see which are free. In this case, only two of the four sites are free. One of these free sites is chosen at random. Note that the conventional Monte Carlo procedure selected from all four adjoining sites at random, irrespective of whether it is occupied or not. A Rosenbluth weight for the move is then calculated. The Rosenbluth weight for each step i is given by ... 

The configurational bias Monte Carlo method involves three types of move. Two of these are translational or rotational moves of the entire molecule, which are performed in the conventional way. The third type of move is a conformational change. A chain is selected at random and one of the segments within it is also randomly chosen. That part of the chain that lies above or below the segment (chosen with equal probability) is discarded and an... 

Martin M G and J I Siepmann 1999. Novel Configurational-bias Monte Carlo Method tor Branched Molecules Transferable Potentials for Phase Equilibria. 2 United-atom Description of Branched Alkanes Journal of Physical Chemistry 103 4508-4517 Metropolis N, A W Rosenbluth, M N Rosenbluth, A H Teller and E Teller 1953 Equation of State Calculations by Fast Computing Machines. Journal of Chemical Physics 21 1087-1092 Okamoto Y and U H E Hansmann 1995. Thermodynamics of HeUx-coU Transitions Studied by Multicanomcal Algorithms. Journal of Physical Chemistry 99 11276-11287 Panagiotopoulos A Z 1987. Direct Determination of Phase Coexistence Properties of Fluids by Monte Carlo Simulation in a New Ensemble. Molecular Physics 61.813-826 Pangali C, M Rao and B J Berne 1978 On a Novel Monte Carlo Scheme for Simulating Water and Aqueous Solutions Chemical Physics Letters 55 413-417. 

Panagiotopoulos and coworkers [51] use the same parameters as Larson for the study of phase behavior, but with two different simulation methodologies. The first technique is the Gibbs ensemble method, in which each bulk phase is simulated in a separate cell and molecules are interchanged and volumes adjusted between the two for equilibration of the system [52]. The second is a standard canonical ensemble simulation, like Larson s, but employs the configurational bias Monte Carlo method. The configurational bias Monte Carlo method is much more efficient than the ones based on reptation and other local moves but is not useful if any dynamic information is sought from the simulations. 

Martin MG, Siepmann 11 (1999) Novel configurational-bias Monte Carlo method for branched molecules. Transferable potentials for phase equilibria. 2. United-atom description of branched alkanes. J Phys Chem B 103 4508-4517... 

Shelley JC, Patey GN (1995) A configuration bias Monte-Carlo method for water. J Chem Phys 102 7656-... 

Siepmann, J.I. Wick, C.D. Self-adapting lixed-end-point configurational-bias Monte Carlo method for the regrowth of interior segments of chain molecules with strong intramolecular interactions. Macromolecules 2000, 33 (19), 7207-7218. 

Flexible Polyelectrolyte Simulations at the Poisson-Boltzmann Level A Comparison of the Kink-Jump and Multigrid Configurational-Bias Monte Carlo Methods. 

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