Binary mixture, parameter

Appendix C presents properties and parameters for 92 pure fluids and characteristic binary-mixture parameters for 150 binary pairs. [Pg.143]

The binary mixture parameter has been fitted to VLE data for 29 systems its values are in Table 1. It should be noted that is independent of temperature and always very close to unity. The calculation of phase equilibria was performed by means of the algorithm of Deiters [8, 9], The reproduction of VLE data and the predictions of LLE data, of excess volumes, of virial coefficients are very good for all 29 binary mixtures investigated [3]. [Pg.407]

Using eqs. (l)-(9), along with empirical pure-electrolyte parameters 3 ), 3 > 3 and and binary mixture parameters 0, one can reproduce experimental activity-coefficient data typically to a few percent and in all cases to + 20%. Of course, as noted above, the most accurate work on complex, concentrated mixtures requires that one include further mixing parameters and also for calculations at temperatures other than 25°C, include the temperature dependencies of the parameters. However, for FGD applications, a more important point is that Pitzer1s formulation appears to be a convergent series. The third virial coefficients... [Pg.61]

Tbe basic scheme for modeling the phase behavior of binary mixtures is first to input the pure component characteristic parameters Tc, Pc, and to, and then determine the binary mixture parameters, kj. and iij., by fitting data such as pressure-composition isotherms. Normally k.. and tIj. are expected to be lie between 0.200. If the two species are close in chemical ize and intermolecular potential, the binary mixture parameters will have values very close to zero. In certain cases a small value of either of these two parameters can have a large influence on the calculated results. [Pg.463]

The data base contains provisions for a simple augmentation by up to eight additional compounds or substitution of other compounds for those included. Binary interaction parameters necessary for calculation of fugacities in liquid mixtures are presently available for 180 pairs. [Pg.5]

While the phase rule requires tliree components for an unsymmetrical tricritical point, theory can reduce this requirement to two components with a continuous variation of the interaction parameters. Lindli et al (1984) calculated a phase diagram from the van der Waals equation for binary mixtures and found (in accord with figure A2.5.13 that a tricritical point occurred at sufficiently large values of the parameter (a measure of the difference between the two components). [Pg.659]

Figure A3.3.2 A schematic phase diagram for a typical binary mixture showmg stable, unstable and metastable regions according to a van der Waals mean field description. The coexistence curve (outer curve) and the spinodal curve (iimer curve) meet at the (upper) critical pomt. A critical quench corresponds to a sudden decrease in temperature along a constant order parameter (concentration) path passing through the critical point. Other constant order parameter paths ending within tire coexistence curve are called off-critical quenches.

In both cases the late stages of kinetics show power law domain growth, the nature of which does not depend on the mitial state it depends on the nature of the fluctuating variable(s) which is (are) driving the phase separation process. Such a fluctuating variable is called the order parameter for a binary mixture, tlie order parameter o(r,0 is tlie relative concentration of one of the two species and its fluctuation around the mean value is 5e(/,t) = c(r,t) - c. In the disordered phase, the system s concentration is homogeneous and the order... [Pg.732]

Here we shall consider two simple cases one in which the order parameter is a non-conserved scalar variable and another in which it is a conserved scalar variable. The latter is exemplified by the binary mixture phase separation, and is treated here at much greater length. The fonner occurs in a variety of examples, including some order-disorder transitions and antrferromagnets. The example of the para-ferro transition is one in which the magnetization is a conserved quantity in the absence of an external magnetic field, but becomes non-conserved in its presence. [Pg.732]

In summary, a combination of the plot based on equation (10.6), using any single substance, and determination of the asymptote (10.14), using any pair of substances, provides a sound means of evaluating the parameters K, tC and. Having found these, further experimental points on (10.6) and (10.15), and possibly also (10.7), provide a check on the adequacy of the dusty gas model. Provided attention is limited to binary mixtures, this check can be quite comprehensive. In their published paper Gunn and King... [Pg.93]

The special appeal of this approach is that it allows the heat of mixing to be estimated in terms of a single parameter assigned to each component. This considerably simplifies the characterization of mixing, since m components (with m 6 values) can be combined into m(m - l)/2 binary mixtures, so a considerable data reduction follows from tabulating 6 s instead of AH s. Table 8.2 is a list of CED and 6 values for several common solvents, as well as estimated 6 values for several common polymers. [Pg.526]

Most of the assumptions are based on idealized models, indicating the limitations of the mathematical methods employed and the quantity and type of experimental data available. For example, the details of the combinatorial entropy of a binary mixture may be well understood, but modeling requires, in large measure, uniformity so the statistical relationships can be determined. This uniformity is manifested in mixing rules and a minimum number of adjustable parameters so as to avoid problems related to the mathematics, eg, local minima and multiple solutions. [Pg.252]

Binary interaction parameters are determined for each pq pair p q) from experimental data. Note that = k and k = k = 0. Since the quantity on the left-hand side of Eq. (4-305) represents the second virial coefficient as predicted by Eq. (4-231), the basis for Eq. (4-305) lies in Eq. (4-183), which expresses the quadratic dependence of the mixture second virial coefficient on mole fraction. [Pg.538]

Another important parameter is the eluent composition. Binary mixtures (and obviously pure solvents) should be preferred to complex mixtures, since new systems perform an on-line analysis of the composition of binary eluents. These eluent systems allow the automatic eluent recycling, with a reduced number of controls. [Pg.277]

The parameters A, B,. .., depend on temperature but not on pressure, and must be determined from experimental data for the binary mixture. [Pg.169]

Although (5 varies with temperature, the quantity [<5, — 5] is insensitive to temperature the solubility parameters used in Eq. (70) were therefore treated as constants. Table III gives some of the solubility parameters used by Chao and Seader. For supercritical components, the solubility parameters were back-calculated from binary-mixture data, as was also done by Shair (P2). [Pg.174]

The difficulties encountered in the Chao-Seader correlation can, at least in part, be overcome by the somewhat different formulation recently developed by Chueh (C2, C3). In Chueh s equations, the partial molar volumes in the liquid phase are functions of composition and temperature, as indicated in Section IV further, the unsymmetric convention is used for the normalization of activity coefficients, thereby avoiding all arbitrary extrapolations to find the properties of hypothetical states finally, a flexible two-parameter model is used for describing the effect of composition and temperature on liquid-phase activity coefficients. The flexibility of the model necessarily requires some binary data over a range of composition and temperature to obtain the desired accuracy, especially in the critical region, more binary data are required for Chueh s method than for that of Chao and Seader (Cl). Fortunately, reliable data for high-pressure equilibria are now available for a variety of binary mixtures of nonpolar fluids, mostly hydrocarbons. Chueh s method, therefore, is primarily applicable to equilibrium problems encountered in the petroleum, natural-gas, and related industries. [Pg.176]

Thermodynamic models are widely used for the calculation of equilibrium and thermophysical properties of fluid mixtures. Two types of such models will be examined cubic equations of state and activity coefficient models. In this chapter cubic equations of state models are used. Volumetric equations of state (EoS) are employed for the calculation of fluid phase equilibrium and thermophysical properties required in the design of processes involving non-ideal fluid mixtures in the oil and gas and chemical industries. It is well known that the introduction of empirical parameters in equation of state mixing rules enhances the ability of a given EoS as a tool for process design although the number of interaction parameters should be as small as possible. In general, the phase equilibrium calculations with an EoS are very sensitive to the values of the binary interaction parameters. [Pg.226]

The expression for the fugacity of a component j in a gas or liquid mixture, fj, based on the Trebble-Bishnoi EoS is available in the literature (Trebble and Bishnoi, 1988). This expression is given in Appendix 1. In addition the partial derivative, (dlnf/dx j>P, for a binary mixture is also provided. This expression is very useful in the parameter estimation methods that will be presented in this chapter. [Pg.231]

It is assumed that there are available NCP experimental binary critical point data. These data include values of the pressure, Pc, the temperature, Tc, and the mole fraction, xc, of one of the components at each of the critical points for the binary mixture. The vector k of interaction parameters is determined by fitting the EoS to the critical data. In explicit formulations the interaction parameters are obtained by the minimization of the following least squares objective function ... [Pg.261]

Several activity coefficient models are available for industrial use. They are presented extensively in the thermodynamics literature (Prausnitz et al., 1986). Here we will give the equations for the activity coefficients of each component in a binary mixture. These equations can be used to regress binary parameters from binary experimental vapor-liquid equilibrium data. [Pg.275]

For each binary mixture there are two adjustable parameters. t 2 and t2). These in turn, are given in terms of characteristic energies All 12 —1LI 12—1 22 and Au21=u2,-un given by... [Pg.278]

The variation of enthalpy for binary mixtures is conveniently represented on a diagram. An example is shown in Figure 3.3. The diagram shows the enthalpy of mixtures of ammonia and water versus concentration with pressure and temperature as parameters. It covers the phase changes from solid to liquid to vapour, and the enthalpy values given include the latent heats for the phase transitions. [Pg.73]

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