Phase prediction

Figure 4 shows experimental and predicted phase equilibria for the acetonitrile/benzene system at 45°C. This system exhibits moderate positive deviations from Raoult s law. The high-quality data of Brown and Smith (1955) are very well represented by the UNIQUAC equation. 

As the conditions of pressure and temperature vary, the phases in which hydrocarbons exist, and the composition of the phases may change. It is necessary to understand the initial condition of fluids to be able to calculate surface volumes represented by subsurface hydrocarbons. It is also necessary to be able to predict phase changes as the temperature and pressure vary both in the reservoir and as the fluids pass through the surface facilities, so that the appropriate subsurface and surface development plans can be made. 

Agatonovic-Kustrin S, Alany RG. Role of genetic algorithms and artificial neural networks in predicting phase behaviour of colloidal delivery systems. Pharm Res 2001 18 1049-55. 

The NRTL equation developed by Renon and Prausnitz overcomes the disadvantage of the Wilson equation in that it is applicable to immiscible systems. If it can be used to predict phase compositions for vapour-liquid and liquid-liquid systems. 

A methodology is described to predict the site of metabolism and the potential MBI by CYPs for compounds as well as subsequent possible phase II metabolism by UGTs. On average, for about 85% of the cases, the method predicted the right site of metabolism within the first two atoms in the ranking list and for more than 80% of the MBI inhibitors. The same methodology can also be applied to predict phase II, UGT-mediated metabolism. 

Within the past few years the advances made in hydrocarbon thermodynamics combined wtih increased sophistication in computer software and hardware have made it quite simple for engineers to predict phase equilibria or simulate complex fractionation towers to a high degree of accuracy through software systems such as SSI s PROCESS, Monsanto s FLOWTRAN, and Chemshare s DISTILL among others. This has not beem the case for electrolyte systems. 

We believe that the PFGC equation of state approach will be the most fruitful new route to predicting phase behavior of the diverse systems encountered in the natural gas/petroleum/coal liquefaction gasification process industry. We commend it to your attention. 

Two-constant equation of state phase behavior calculations for aqueous mixtures often require the use of temperature dependent binary interaction parameters. The methods used for evaluating these parameters for some of the typical aqueous binary pairs found in coal gasification and related process streams are described. Experimental and predicted phase compositions based on these methods are illustrated for aqueous pairs containing CO2. H2S, NH3, and other gases. 

As a conclusion to these notes on the assessment and compilation of intermetallic data, we mention a few examples of papers in which criteria to be followed in order to extract from literature data the best version of a phase diagram have been discussed. These are Morral and Gupta (1991) (a figure of merit for predicted phase diagram), Okamoto and Massalski (1991, 1993) (thermodynamically improbable phase diagrams and guidelines for binary phase diagram assessment). See also various comments in several chapters in Cahn (2001). 

A general presentation and discussion of the origin of structure of crystalline solids and of the structural stability of compounds and solid solutions was given by Villars (1995) and Pettifor (1995). For an introduction to the electronic structure of extended systems, see Hoffmann (1987, 1988). In this chapter a brief sampling of some useful semi-empirical correlations and, respectively, of methods of classifying (predicting) phase and structure formation will be summarized. 

Quantities useful for predicting phase continuity and inversion in a stirred, sheared, or mechanically blended two-phased system include the viscosities of phases 1 and 2, and and the volume fractions of phases 1 and 2, and ij. (Note These are phase characteristics, not necessarily polymer characteristics.) A theory was developed predicated on the assumption that the phase with the lower viscosity or higher volume fraction will tend to be the continuous phase and vice versa (23,27). An idealized line or region of dual phase continuity must be crossed if phase inversion occurs. Omitted from this theory are interfacial tension and shear rate. Actually, low shear rates are implicitly assumed. 

A particular complex problem has been the modelling of Si/W(l 10) Amar et have included pairwise interactions up to the sixth nearest neighbor shell, as estimated experimentally from field-ion microscopic studies The predicted phase diagram (Fig. 30) exhibits (5 x 1), (6 x 1) and p(2 x 1) commensurate phases, as well as a broad regime of an incommensurate phase. In contrast to the ANNNI model the present model does seem to have a finite-temperature Lifshitz point, where the incommensurate, commensurate... 

Similarly, quantitative structure-metabolism relationships (QSMR) have been studied [42]. QSAR tools, such as pattern recognition analysis, have been used to e. g. predict phase II conjugation of substituted benzoic acids in the rat [53]. 

Clearly CALPHAD has now come of age and is at a watershed where complex phase equilibria calculations can now be performed as a routine operation and yet have also been placed on a sound physical basis. Computer programmes exist which can perform complex calculations on a PC and which can therefore be operated at any location without extensive prior expertise. Furthermore, it is possible in many cases to predict phase equilibria in multi-component alloys to a degree which is close to that expected from experiment (see Chapter 10). It is therefore a branch of science that is mature and, indeed, has already entered the next stage of development, which emphasises the need to concentrate on extending its range of applicability. 

Figure 7.17. Predicted phase diagiam for the system (CiiInSe2)i-x(ZnSe)2i (a) stable and metastable equilibrium between dialcopyrite (CH) and zinc-blende (ZB) phases using volume-dependent interaction parameters (b) using a hierarchy of less accurate tqiproximations (<)sorio el al. 1993).

Figure 7.18. Comparison of experimental and predicted phase equilibria in the system CaC03-MgC03 using CVM in the tetrahedron approximation for a trigonally distorted f.c.c. Ising lattice. Semi-quantitative agreement is achieved for the calcite-dolomite segment but the Mg-rich side of the diagram indicates the need to include a more complex model (Burton and Kikuchi 1984b).

Aluminium alloys form one of the most widely used groups of materials in existence. They make products which are often cheap and can be applied to many different areas. Extensive work has been done on the experimental determination of binary and ternary phase diagrams, mainly during the mid-part of this century, and researchers such as Phillips (1961) and Mondolfo (1976) have produced detailed reviews of the literature which provide industry standard publications. However, although some important Al-alloys are based on ternary systems, such as the LM2S/ 356 casting alloy based on Al-Mg-Si, in practice they inevitably include small amounts of Cu, Mn, Fe, Ti etc., all of which can significantly modify the castability and properties of the final product. The situation is further exacerbated by the use of scrap material. It is therefore useful to be able to predict phase equilibria in multi-component alloys. 

Three unknown samples are examined in the prediction phase. The results of a three nearest-neighbor classification are unknown 1 = PET unknown 2 = PET unknown 3 = PVC. 

The strengths of the factor-based methods lie in the fact that they are multivariate. The diagnostics are excellent in both the calibration and prediction phases. Improved precision and accuracy over univariate methods can often be realized because of the multivariate advantage. Ultimately, PLS and PCR are able to model complex data and identify when the models are no longer valid. This is an extremely powerful combination. 

Used to determine a cutoff value for use in the prediction phase. 

Summary of Prediction Diagnostic Tools for SIMCA From the prediction diagnostics, the conclusion is that unknow.as 1 and 4 do not belong to either of the TEA or MEK classes. Sample 3 is a member of the TEA class and sample 2 is a member of the MEK class. There is considerable reliability in the classifications due to the large values for the excluded samples both in the validation and prediction phases. The residuals and score plots are consistent with the values. 

The advantages of these methods are based on their simplicit - tlie number of samples required to construct the models is relatively small, statistics are available that can be used to validate the models, and it is easier to describe these methods to the users of the models. The classical methods are also multivariate in nature and, therefore, have good diagnostics tools that can be used to detect violations of the assumptions both during the calibration and prediction phases. 

Figure 2.41 Predicted phase diagram for cell-cell adhesion. Reprinted, by permission, from D. A. Lauffenburger and J. J. Linderman, Receptors, p. 281. Copyright 1993 by Oxford University Press.

---