Molecular engineering calculations using

The preceding equations, which have assumed that both the air and the water vapor benave as ideal gases, are sufficiently accurate for most engineering calculations. If it is desired to remove the restriction that water vapor oehave as an ideal gas, the aclual density ratio should be used in place of the molecular-weight ratio in Eqs. (12-5) and (12-6). 

The latest versions of the DfW software incorporate a reasoning engine that uses log P (calculated by a C log P plug-in) and molecular mass to predict the likelihood that a chemical will express its potential toxicity regarding a specific endpoint in the selected species. This feature is, for example, used in the... 

For process engineering calculations it is almost inevitable that experimental values of D or f), even if available in the literature, will not cover the entire range of temperature, pressure, and concentration that is of interest in any particular application. It is, therefore, important that we be able to predict these coefficients from fundamental physical and chemical data, such as molecular weights, critical properties, and so on. Estimation of gaseous diffusion coefficients at low pressures is the subject of Section 4.1.1, the correlation and prediction of binary diffusion coefficients in liquid mixtures is covered in Sections 4.1.3-4.1.5. We do not intend to provide a comprehensive review of prediction methods since such are available elsewhere (Reid et al., 1987 Ertl et al., 1974 Danner and Daubert, 1983) rather, it is our purpose to present a selection of methods that may be useful in engineering calculations. 

A general definition of the Quantum Molecular Similarity Measure is reported. Particular cases of this definition are discussed, drawing special attention to the new definition of Gravitational-like Quantum Molecular Similarity Measures. Applications to the study of fluoromethanes and chloro-methanes, the Carbonic Anhydrase enzyme, and the Hammond postulate are presented. Our calculations fully support the use of Quantum Molecular Similarity Measums as an efficient molecular engineering tool in order to predict physical properties, lMok>gical and pbarraacdogical activities, as well as to interpret complex chemical problems. 

Clydesdale, G. Docherty, R. Roberts, K. J., Computational Studies of the Morphology of Molecular Crystals Through Solid State Intermolecular Force Calculations Using the Atom-Atom Method. In Colloid and Surface Engineering Controlled Particle, Droplet and Bubble Formation-, Wedlock, D. J., Ed. Butterworth Heinman London, 1994 pp. 95-135. 

Molecular simulation using realistic force fields provides a reliable prediction of diffusion coefficient (D). However, it is computationally expensive and cannot be used for routine engineering calculations. An alternative approach is to develop phenomenological correlations that represent accurately experimental or molecular simulation data and can be interpolated or even extrapolated in other range of conditions. In the past, many empirical correlations have been developed with varying degree of success (Wilke and Chang (1955), Leahy-Dios and Firoozabadi (2007), Matthews et al. (1987) and Erkey et al. (1990)) [10] [13] [6]. 

As depicted in Figure 1.4, there is a direct link between time and size scale, from which it is obvious that the micro and macro scales are not related to the same time scale [20], As an example, molecular dynamics calculations are addressing a time scale in the order of femto- to nanoseconds, whereas process system integration evolves on the scale of years. Engineers have traditionally been working at the meso scale, which is represented by the middle portion of Figure 1.4, using phe-... 

In process engineering, moles are used extensively in performing (lie calculations. A mole is defined as that mass of a substance that is numen cally equal to its molecular weight. Avogadro s Law states that identical volumes of gas at the same temperature and pressure contain equal numbers of molecules for each gas. It can be reasoned that these identical volumes will have a weight proportional to the molecular weight of the gas. If the mass is expressed as... 

One must understand the physical mechanisms by which mass transfer takes place in catalyst pores to comprehend the development of mathematical models that can be used in engineering design calculations to estimate what fraction of the catalyst surface is effective in promoting reaction. There are several factors that complicate efforts to analyze mass transfer within such systems. They include the facts that (1) the pore geometry is extremely complex, and not subject to realistic modeling in terms of a small number of parameters, and that (2) different molecular phenomena are responsible for the mass transfer. Consequently, it is often useful to characterize the mass transfer process in terms of an effective diffusivity, i.e., a transport coefficient that pertains to a porous material in which the calculations are based on total area (void plus solid) normal to the direction of transport. For example, in a spherical catalyst pellet, the appropriate area to use in characterizing diffusion in the radial direction is 47ir2. 

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