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Monte Carlo molecular simulation is applied to calculate miscibility behavior of a valence force-field model of InGaN alloy as a function of temperature. Calculations find that the upper critical solution temperature is 1550 K, in good agreement with previous studies based on regular solution theory. The simulations show that the excess entropy is small, and the excess enthalpy is insensitive to temperature, indicating that the regular-solution treatment is appropriate for this system.

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Molecular simulations are conducted to determine the limits of miscibility of a valence force field model for zinc-blende-structured In 1ϪxϪy Ga x Al y N semiconductor alloys. The transition matrix Monte Carlo method is used to calculate the free energy of the model alloys as a function of temperature and alloy composition ͑considering both x and y ranging from zero to unity͒. Analysis of the free-energy surface provides values for the upper critical solution temperature of the ternary alloys: InGaN ͑1550 K͒, InAlN ͑2700 K͒, and GaAlN ͑195 K͒. The miscibility envelope of the quaternary alloy is determined at 773 K and 1273 K. The excess properties of the mixtures are calculated, and it is found that the excess entropy is negligible, and the excess enthalpy is nearly independent of temperature. Consequently, regular-solution theory provides a good description of the thermodynamic properties of the alloys, and comparison of the simulation results with the phase behavior previously reported using regular-solution theory finds good agreement. Structural properties of the ternary compounds are examined in terms of the local compositions. For InGaN it is found ͑surprisingly͒ that there is a slight preference for In atoms to have Ga atoms rather than other In atoms as neighbors, in comparison to a random mixture. The two other ternary compounds exhibit the expected behavior, in which the ͑small͒ deviations from random mixing tend to favor segregation of like atoms. Among the ternaries, GaAlN is found to show the greatest deviations from random mixing.

This paper provides a review of the available literature on computational schemes for rational solvent design, with a focus on solvent extraction and crystallization (the two most common unit operations) in pharmaceutical industry. The computer-aided design of solvents is important as a cost-effective tool, especially with the regular development of new pharmaceutical molecules. Also, there is a need to minimize the amount and the number of solvents used with regard to environmental, health, and toxicological concerns. This review covers the properties of interest and the predictive methods for estimation of these properties in solvent design including the group contribution based methods, quantitative structure property prediction methods and molecular modeling methods. In addition, the various optimization approaches for rational solvent design such as outer approximation, branch and bound, simulated annealing, and genetic algorithm are also discussed.