Monte sequential simulation

Monte Carlo/simulated annealing (MC/SA) algorithm for sequential assignment in uniformly 13C, 15N-labeled proteins [137]. The two-dimensional (2D) NCACX and NCOCX spectra measured for the fibril samples of full-length Syrian hamster prion protein (residues 23-231) have been analyzed by the MC/SA protocol, from which it has been concluded that the fibril core is formed primarily in the region of residues 173-224 [54]. 

The area available to a disk (or to a sphere) to be adsorbed on a surface during a random sequential adsorption (RSA) of a binary mixture of disks (spheres) is in general estimated via Monte-Carlo simulations, which are vety time consuming. A simple analytical expression is proposed, which provides good estimates of the jamming points for the RSA of a binary mixture of disks or spheres. The predictions of the simple formula have been compared with the Monte-Carlo simulations existing in the literature [8.10],... 

A simple analytical expression is proposed for the area available to a disk on a surface for a Random Sequential Adsorption (RSA) of binary mixtures of disks. The expression was obtained by combining the low-order terms of the density expansion of the available area with the asymptotic behaviour of the surface coverage near the jamming point. Comparison with Monte Carlo simulations shows that this approach provides a fair estimation of the jamming coverage for both kinds of disks. 

The RSA model received renewed attention after Feder [12] observed that the adsorption on the surface of apo-ferritin molecules (large iron-storage proteins with a diameter of about 10 nm), which adsorb irreversibly, reached saturation at a coverage (k = 0.518. Monte Carlo simulations of Random Sequential Adsorption of disks on a surface last prohibitively long in the vicinity of the jamming point however Feder [12] noted that in the vicinity of the jamming coverage, 9 has a power-law dependence on time ... 

These estimates were compared to the Monte Carlo simulations available in literature for the Random Sequential Adsorption of a binary mixture of disks and spheres. 

Figure 6. The average energy of the water of hydration of the triclinic lysozyme crystal as a function of the number of configurations generated in the Monte Carlo simulation. The upper curve (A) corresponds to the cumulative statistical average, and the lower curve fU gives the statistical average over sequential sets of 5,000...

An approach based on the sequential use of Monte Carlo simulation and Quantum Mechanics is suggested for the treatment of solvent effects with special attention to solvatochromic shifts. The basic idea is to treat the solute, the solvent and its interaction by quantum mechanics. This is a totally discrete model that avoids the use of a dielectric continuum. Statistical analysis is used to obtain uncorrelated structures. The radial distribution function is used to determine the solvation shells. Quantum mechanical calculations are then performed in supermolecular structures and the spectral shifts are obtained using ensemble average. Attention is also given to the case of specific hydrogen bond between the solute and solvent. 

Fault Trees are static—they provide a picture of a system independent of time. The method has trouble with dynamic systems, where certain events trigger other events sequentially, or where there is a time delay between the occurrence of two events. For these situations another method, such as a Monte Carlo simulation, may be a better choice. 

The calculation is executed by using the sequential Monte Carlo simulation technique. For both branches and nodes are used these reliability parameters ... 

Billinton R., Wangdee W. 2006. Delivery Point Reliability Indices of a Bulk Electric System Using Sequential Monte Carlo Simulation. IEEE Transactions on Power Delivery, 21(1), Pages 345 -352... 

Youk J H and Jo W H (2001) Origin of miscibility-induced sequential reordering and crystallization-induced sequential reordering in binary copolyesters A Monte Carlo simulation, J Polym Sci Part... 

Flowchart of a kinetic Monte Carlo simulation of the sequential evaporation of an atomic cluster in which the size, internal energy and momenta of the main fragment are monitored as a function of time. 

Some recent dynamic Monte Carlo simulations have also reported increases in chain dimensions in filled systems [67]. There have been several reports of simulations, however, that have yielded results in disagreement with the described simulations and the two corresponding scattering reports mentioned above. The major difference in approach was the use of dense collections of chains instead of single chains sequentially generated in the vicinities of the filler... 

Summary. The underpotential deposition (UPD) of metal sub-monolayers and monolayers on metal substrates for the systems Ag/Au(100), Au/Ag(100), Ag/Pt(100), Pt/Ag(100), Au/Pt(100), Pt/Au(100), Au/Pd(100), and Pd/Au(100) is studied by means of lattice Monte Carlo simulations. Interaction energies among different metal atoms are evaluated by using the embedded-atom method. A wide variety of physical situations are found and discussed, including systems exhibiting the sequential adsorption of atoms on kink and step sites, prior to the completion of the monolayer. On the other hand, for other systems, we observe the formation of 2D alloys... 

The preceding discussion applied implicitly to what we classify as dynamical simulations — namely, those simulations in which all correlations in the final trajectory arise because each configuration is somehow generated from the previous one. This time-correlated picture applies to a broad class of algorithms MD, Langevin and Brownian dynamics, as well as traditional Monte Carlo (MC, also known as Markov-chain Monte Carlo). Even though MC may not lead to true physical dynamics, all the correlations are sequential. 

Simulation techniques suitable for the description of phenomena at each length-scale are now relatively well established Monte Carlo (MC) and Molecular Dynamics (MD) methods at the molecular length-scale, various mesoscopic simulation methods such as Dissipative Particle Dynamics (Groot and Warren, 1997), Brownian Dynamics, or Lattice Boltzmann in the colloidal domain, Computational Fluid Dynamics at the continuum length-scale, and sequential-modular or equation-based methods at the unit operation/process-systems level. 

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