Monte Carlo methodology

Valleau, J. P. Temperature-and-density-scaling Monte-Carlo methodology and the canonical thermodynamics of Lennard-Jonesium. Mol. Sim. 2005, 31, 223-253... 

In chapter 3, Profs. A. Gonzalez-Lafont, Lluch and Bertran present an overview of Monte Carlo simulations for chemical reactions in solution. First of all, the authors briefly review the main aspects of the Monte Carlo methodology when it is applied to the treatment of liquid state and solution. Special attention is paid to the calculations of the free energy differences and potential energy through pair potentials and many-body corrections. The applications of this methodology to different chemical reactions in solution are... 

As noted in Sections 3.1 and 4.1, the atmospheric relevance of the two acids often extends beyond the issue of their surface dissociation in the conditions that we have considered here. Thus, for example, the widely occurring sulfate aerosols are concentrated sulfuric acid solutions and nitric acid trihydrate (NAT) is also clearly fairly concentrated. Elucidation of the acid ionization state of such aerosol surfaces—and thus the theoretical characterization of the mechanisms and rates of chemical reaction occurring on them—requires other tools to deal with the multiple proton transfer possibilities present in these systems. One such tool, a generalization of available reaction Monte Carlo methodologies [72] to treat such multiple proton transfers, is under development [73]. 

Gr will arise merely as consequences of a Construction Principle (CP) and of the maximum randomness size-assignation procedure applied to simulate the network from these distributions. Second, a general Monte Carlo methodology will be implemented to represent three-dimensional (3D) networks where H, Co, C and Gr coexist. Third, a simulation of the condensation-evaporation characteristics of a fluid within the simulated 3D networks will be performed. 

Hansen, E., Neurock, M. First-principles-based Monte Carlo methodology applied to O/Rh(100). Surf. Sci. 2000, 464, 91-107. 

Irizarry, R. 2008a Fast Monte Carlo methodology for multivariate particulate systems I point ensemble Monte Carlo. Chemical Engineering Science 63, 95-110. 

J. S. Evans, A. M. Mathiowetz, S. I. Chan, W. A. Goddard, 3rd. De novo prediction of polypeptide conformations using dihedral probability grid Monte Carlo methodology. Protein Sci. 1995, 4, 1203-1216. 

Frolov Your technique has been applied to unconfined constant-pressure flow conditions. What is really interesting for propulsion is the confined reactive flow with acoustic interactions, pressure gradients, etc. At your viewgraph regarding future work, I did not see any plan of using Monte-Carlo methodology to confined conditions. Can you use this technique for confined flow with pressure coupling ... 

Variational Monte Carlo (or VMC, as it is now commonly called) is a method that allows one to calculate quantum expectation values given a trial wavefunction [1,2]. The actual Monte Carlo methodology used for this is almost identical to the usual classical Monte Carlo methods, particularly those of statistical mechanics. Nevertheless, quantum behavior can be studied with this technique. The key idea, as in classical statistical mechanics, is the ability to write the desired property <0> of a system as an average over an ensemble... 

The feature that separates Monte Carlo methodology from deterministic methods is mainly the use of random numbers or pseudorandom number sequences in the algorithm. The use of random number differs in the various Monte Carlo methods. A simple Monte Carlo method can be programmed in a few lines of coding or by using existing software, while a general-purpose routine can be quite complicated. 

The feature that separates Monte Carlo methodology from deterministic methods is mainly the use of random numbers, or pseudo-random number sequences in the algo-... 

Bordere, S. (2002). Original Monte Carlo methodology devoted to the study of sintering processes. J. Am Ceram. Soc., Vol. 85, No. 7, pp. 1845-1852 Braginsky, M. Tikare, V. Olevsky, E. (2005). Numerical simulation of solid state sintering. 

Methods using genetic algorithms or Monte Carlo methodologies are similar in some respects to atom buildup procedures in that there is no inherent restriction on the diversity available to the programs. Specialized constraints are required, however, to deal with problems of synthetic accessibility and to restrict the solution space searched by the algorithms. 

Thermodynamically Guided Atomistic Monte Carlo Methodology for Generating Realistic Shear Flows... 

The general idea behind all Monte Carlo methodologies is to provide an efficient stochastic sampling of the configurational or conformational phase space or parts of it with the... 

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