Monte Carlo simulation prediction

For polymer chains in two dimensions in good solvents, the theoretical predictions point to a v value narrowly centered in 0.75 [61], Monte Carlo simulations predicts a value of 0.753 [66], while by the matrix-transfer method a value of 0.7503 is predicted. In the case of theta condition the situation is not clear, the predictions are less precise. Monte Carlo simulation [66] has suggested ve 0.51 while matrix-transfer data suggest ve 0.55 [67],... 

One application of the grand canonical Monte Carlo simulation method is in the study ol adsorption and transport of fluids through porous solids. Mixtures of gases or liquids ca separated by the selective adsorption of one component in an appropriate porous mate The efficacy of the separation depends to a large extent upon the ability of the materit adsorb one component in the mixture much more strongly than the other component, separation may be performed over a range of temperatures and so it is useful to be to predict the adsorption isotherms of the mixtures. 

Gdanitz, R J 1992. Prediction of Molecular Crystal Stluctures by Monte Carlo Simulated Annealing Without Reference to Diffraction Data. Chemical Physics Letters 190 391-396. 

Surface tension is usually predicted using group additivity methods for neat liquids. It is much more difficult to predict the surface tension of a mixture, especially when surfactants are involved. Very large molecular dynamics or Monte Carlo simulations can also be used. Often, it is easier to measure surface tension in the laboratory than to compute it. 

Monte Carlo simulations are an efficient way of predicting liquid structure, including the preferred orientation of liquid molecules near a surface. This is an efficient method because it is not necessary to compute energy derivatives, thus reducing the time required for each iteration. The statistical nature of these simulations ensures that both enthalpic and entropic effects are included. 

Figure 6 shows the field dependence of hole mobiUty for TAPC-doped bisphenol A polycarbonate at various temperatures (37). The mobilities decrease with increasing field at low fields. At high fields, a log oc relationship is observed. The experimental results can be reproduced by Monte Carlo simulation, shown by soHd lines in Figure 6. The model predicts that the high field mobiUty follows the following equation (37) where d = a/kT (p is the width of the Gaussian distribution density of states), Z is a parameter that characterizes the degree of positional disorder, E is the electric field, is a prefactor mobihty, and Cis an empirical constant given as 2.9 X lO " (cm/V). ...

RH Smith Jr, WL Jorgensen, J Tirado-Rives, ML Lamb, PAJ Janssen, CJ Michejda, MBK Smith. Prediction of binding affinities for TIBO inhibitors of HIV-1 reverse transcriptase using Monte Carlo simulations m a linear response method. J Med Chem 41 5272-5286, 1998. 

Buonicore, A. J., Monte Carlo Simulation to Predict Collection Efficiencies of Centrifugal Separators," 74tli A.I.Ch.E. Meeting, New Orleans, La., March 1973. 

The model has been treated analytically employing the effective medium approach [58] and by Monte Carlo simulation. It makes the following predictions A dilute ensemble of non-interacting charge carriers, initially generated at random within the DOS, lends to relax toward the tail slates and ultimately equilibrates at... 

The method for estimating parameters from Monte Carlo simulation, described in mathematical detail by Reilly and Duever (in preparation), uses a Bayesian approach to establish the posterior distribution for the parameters based on a Monte Carlo model. The numerical nature of the solution requires that the posterior distribution be handled in discretised form as an array in computer storage using the method of Reilly 2). The stochastic nature of Monte Carlo methods implies that output responses are predicted by the model with some amount of uncertainty for which the term "shimmer" as suggested by Andres (D.B. Chambers, SENES Consultants Limited, personal communication, 1985) has been adopted. The model for the uth of n experiments can be expressed by... 

M. P. Allen, Introduction to Monte Carlo simulations. In Observation, Prediction and Simulation of Phase Transitions in Complex Fluids, M. Bans, L. F. Rull, and J.- P Ryckaert, Eds., Kluwer Academic Publishers, Boston, 1995, 339-356. 

Figure 7.10. Distribution of two adsorbates A and B over a surface with different combinations of attractive and repulsive interactions, as predicted by a Monte Carlo simulation. (Courtesy A.P. van Bavel, Eindhoven.)...

Predictive modeling [38], Tachugi design principles [2], Monte Carlo simulations to simulate impacts of different product and process conditions on Q attribute level [40]... 

---