P. Politzer, J.S. Murray, Computational prediction of condensed phase properties from statistical characterization of molecular surface electrostatic potentials. Fluid Phase Equil. 185, 129-137 (2001) [Pg.164]

This is accordingly a unified approach to representing and predicting condensed phase properties that are determined by noncovalent interactions. We summarize it conceptually as a general interaction properties function (GIPF), Eq. (9) [Pg.26]

We consider a binary two-phase system at temperature T. One phase is a liquid and the other is a solid. Since the effect of pressure on condensed-phase properties is normally negligible at low or moderate pressures, we do not need to specify the pressure. Let component 1 be the liquid solvent and component 2 the solid solute. [Pg.45]

Statistical mechanics computations are often tacked onto the end of ah initio vibrational frequency calculations for gas-phase properties at low pressure. For condensed-phase properties, often molecular dynamics or Monte Carlo calculations are necessary in order to obtain statistical data. The following are the principles that make this possible. [Pg.12]

Volumetric expansion caused by dissolution of CO2 into liquid polymers is accompanied by significant changes in the physical properties of the condensed phase. Properties that change include the melting point, viscosity, interfacial tension, diffusion coefficients, and potentially solubilities of other species and the polarity of the liquid phase. [Pg.681]

The quantities that have been presented do effectively characterize the electrostatic potential on a molecular surface. We have shown that a number of macroscopic, condensed-phase properties that depend upon noncovalent interactions can be expressed in terms of some subset of these quantities (frequently [Pg.26]

Descriptions of classical and quantum mechanical methods for simulating energetic salts are presented. An overview of recent applications of these methods for predictions of gas-and condensed-phase properties, chemical reactivities, and phase transitions is given. The limitations and some suggestions for further developments of the methods are also discussed. [Pg.431]

The most important molecular interactions of all are those that take place in liquid water. For many years, chemists have worked to model liquid water, using molecular dynamics and Monte Carlo simulations. Until relatively recently, however, all such work was done using effective potentials [4T], designed to reproduce the condensed-phase properties but with no serious claim to represent the tme interactions between a pair of water molecules. [Pg.2449]

Computer simulations therefore have several inter-related objectives. In the long term one would hope that molecular level simulations of structure and bonding in liquid crystal systems would become sufficiently predictive so as to remove the need for costly and time-consuming synthesis of many compounds in order to optimise certain properties. In this way, predictive simulations would become a routine tool in the design of new materials. Predictive, in this sense, refers to calculations without reference to experimental results. Such calculations are said to be from first principles or ab initio. As a step toward this goal, simulations of properties at the molecular level can be used to parametrise interaction potentials for use in the study of phase behaviour and condensed phase properties such as elastic constants, viscosities, molecular diffusion and reorientational motion with maximum specificity to real systems. Another role of ab initio computer simulation lies in its interaction [Pg.4]

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