Properties, estimation vapor pressure

Measurements of gas chromatographic retention time are often used as a fast and easy method of estimating vapor pressure. These estimated pressures are related to the gas/substrate partition coefficient, which can be regarded as a ratio of solubility of the substance in the gas to that in the substrate, both solubilities being of the substance in the liquid state. As a result the estimated vapor pressures are of the liquid state. To obtain the solid vapor pressure requires multiplication by the fugacity ratio. It is important to establish if the estimated and reported property is of the vapor or liquid. 

Therefore, similar to the attempts made to estimate vapor pressure (Section 4.4) there have been a series of quite promising approaches to derive topological, geometric, and electronic molecular descriptors for prediction of aqueous activity coefficients from chemical structure (e.g., Mitchell and Jurs, 1998 Huibers and Katritzky, 1998). The advantage of such quantitative structure property relationships (QSPRs) is, of course, that they can be applied to any compound for which the structure is known. The disadvantages are that these methods require sophisticated computer software, and that they are not very transparent for the user. Furthermore, at the present stage, it remains to be seen how good the actual predictive capabilities of these QSPRs are. 

Alternatives to Soave s approach and group contribution adaptations would be better focused on capabilities not offered by such approaches. For example, pure component properties like vapor pressure are assumed to be available when applying Soave s methodology. In the coming world of chemical product design, this assumption may not be satisfactory. Molecular simulation offers the prospect of being able to make these predictions for transport properties as well as equilibrium properties. Proximity effects would also be naturally included within molecular modeling. While the National Research Council has estimated that such predictive capability may not be available for a decade or two, viable preliminary versions may come much sooner than that. 

An additional role in my professional life is a Honorar) Professor position in Durban, South Africa. Currently, my group there consists of 4 MSc students, all highly motivated. We developed and published estimation methods for a number of important properties like vapor pressure, liquid viscosity, water and alkane solubility, etc. The first of our methods on normal boiling point estimation is already generally regarded as the primary and best method available. 

The small differences in physical properties of substances containing elements with isotopes are manifested through mea.surement of isotope ratios. When water evaporates, the vapor is richer in its lighter isotopes ( Hj O) than the heavier one ( Hj O). Such differences in vapor pressures vary with temperature and have been used, for example, to estimate sea temperatures of 10,000 years ago (see Chapter 47). 

An extensive pesticide properties database was compiled, which includes six physical properties, ie, solubiUty, half-life, soil sorption, vapor pressure, acid pR and base pR for about 240 compounds (4). Because not all of the properties have been measured for all pesticides, some values had to be estimated. By early 1995, the Agricultural Research Service (ARS) had developed a computerized pesticide property database containing 17 physical properties for 330 pesticide compounds. The primary user of these data has been the USDA s Natural Resources Conservation Service (formerly the Soil Conservation Service) for leaching models to advise farmers on any combination of soil and pesticide properties that could potentially lead to substantial groundwater contamination. 

Among the techniques employed to estimate the average molecular weight distribution of polymers are end-group analysis, dilute solution viscosity, reduction in vapor pressure, ebuUiometry, cryoscopy, vapor pressure osmometry, fractionation, hplc, phase distribution chromatography, field flow fractionation, and gel-permeation chromatography (gpc). For routine analysis of SBR polymers, gpc is widely accepted. Table 1 lists a number of physical properties of SBR (random) compared to natural mbber, solution polybutadiene, and SB block copolymer. 

Mathematical Consistency. Consistency requirements based on the property of exact differentials can be apphed to smooth and extrapolate experimental data (2,3). An example is the use of the Gibbs-Duhem coexistence equation to estimate vapor mole fractions from total pressure versus Hquid mole fraction data for a binary mixture. 

Example 7 Estimate the Vapor Pressure of Thiophene at 500 K.. . . Example 8 Estimate the Vapor Pressure of Acetaldehyde at 0 C. . . Ideal Gas Thermal Properties. 

In order to ensure thermodynamic consistency, in almost all cases these properties are calculated from Tr. and the vapor pressure and liquid density correlation coefficients listed in those tables. This means that there will be slight differences between the values listed here and those in the DIPPR tables. Most of the differences are less than 1%, and almost all the rest are less than the estimated accuracy of the quantity in question. 

An analytical method for the prediction of compressed liquid densities was proposed by Thomson et al. " The method requires the saturated liquid density at the temperature of interest, the critical temperature, the critical pressure, an acentric factor (preferably the one optimized for vapor pressure data), and the vapor pressure at the temperature of interest. All properties not known experimentally maybe estimated. Errors range from about 1 percent for hydrocarbons to 2 percent for nonhydrocarbons. 

The estimation of the two parameters requires not only conversion and head space composition data but also physical properties of the monomers, e.g. reactivity ratios, vapor pressure equation, liquid phase activity coefficients and vapor phase fugacity coefficients. 

At the fundamental level of equilibrium modeling the advantages are many. The model can combine a number of compartments through simple relationship to describe a realistic environment within which chemicals can be ranked and compared. Primary compartments that chemicals will tend to migrate toward or accumulate in can be identified. The arrangement of compartments and their volumes can be selected to address specific environmental scenarios. Data requirements are minimal, if the water solubility and vapor pressure of a chemical are known, other properties can be estimated, and a reasonable estimate of partitioning characteristics can be made. This is an invaluable tool in the early evaluation of chemical, whether the model be applied to projected environmental hazard or evaluation of the behavior of a chemical in an environmental application, as with pesticides. Finally, the approach is mathematically very simple and can be handled on simple computing devices. 

The major differences between behavior profiles of organic chemicals in the environment are attributable to their physical-chemical properties. The key properties are recognized as solubility in water, vapor pressure, the three partition coefficients between air, water and octanol, dissociation constant in water (when relevant) and susceptibility to degradation or transformation reactions. Other essential molecular descriptors are molar mass and molar volume, with properties such as critical temperature and pressure and molecular area being occasionally useful for specific purposes. A useful source of information and estimation methods on these properties is the handbook by Boethling and Mackay (2000). 

Solubility in water and vapor pressure are both saturation properties, i.e., they are measurements of the maximum capacity that a solvent phase has for dissolved chemical. Vapor pressure P (Pa) can be viewed as a solubility in air, the corresponding concentration C (mol/m3) being P/RT where R is the ideal gas constant (8.314 J/mol.K) and T is absolute temperature (K). Although most chemicals are present in the environment at concentrations well below saturation, these concentrations are useful for estimating air-water partition coefficients as ratios of saturation values. It is usually assumed... 

Saturation properties such as solubility in water and vapor pressure can be measured directly for solids and liquids. For certain purposes it is useful to estimate the solubility that a solid substance would have if it were liquid at a temperature below the melting point. For example, naphthalene melts at 80°C and at 25°C the solid has a solubility in water of 33 g/m3 and a vapor pressure of 10.9 Pa. If naphthalene was a liquid at 25°C it is estimated that its solubility would be 115 g/m3 and its vapor pressure 38.1 Pa, both a factor of 3.5 greater. This ratio of solid to liquid solubilities or vapor pressures is referred to as the fugacity ratio. It is 1.0 at the melting point and falls, in this case at lower temperatures to 0.286 at 25°C. 

As was discussed earlier in Section 1.2.8 a complication arises in that two of these properties (solubility and vapor pressure) are dependent on whether the solute is in the liquid or solid state. Solid solutes have lower solubilities and vapor pressures than they would have if they had been liquids. The ratio of the (actual) solid to the (hypothetical supercooled) liquid solubility or vapor pressure is termed the fugacity ratio F and can be estimated from the melting point and the entropy of fusion. This correction eliminates the effect of melting point, which depends on the stability of the solid crystalline phase, which in turn is a function of molecular symmetry and other factors. For solid solutes, the correct property to plot is the calculated or extrapolated supercooled liquid solubility. This is calculated in this handbook using where possible a measured entropy of fusion, or in the absence of such data the Walden s Rule relationship suggested by Yalkowsky (1979) which implies an entropy of fusion of 56 J/mol-K or 13.5 cal/mol-K (e.u.)... 

The physical properties of -hexane (see Table 3-2) that affect its transport and partitioning in the environment are water solubility of 9.5 mg/L log Kow (octanol/water partition coefficient), estimated as 3.29 Henry s law constant, 1.69 atm-m3 mol vapor pressure, 150 mm Hg at 25 °C and log Koc in the range of 2.90 to 3.61. As with many alkanes, experimental methods for the estimation of the Koc parameter are lacking, so that estimates must be made based on theoretical considerations (Montgomery 1991). 

Basak, S. C. and Mills, D. Quantitative structure-property relationships (QSPRs) for the estimation of vapor pressure A hierarchical approach using mathematical structural descriptors. J. Chem. Inf. Comput. Sci. 2001, 41, 692-701. 

The enthalpies of phase transition, such as fusion (Aa,s/f), vaporization (AvapH), sublimation (Asut,//), and solution (As n//), are usually regarded as thermophysical properties, because they referto processes where no intramolecular bonds are cleaved or formed. As such, a detailed discussion of the experimental methods (or the estimation procedures) to determine them is outside the scope of the present book. Nevertheless, some of the techniques addressed in part II can be used for that purpose. For instance, differential scanning calorimetry is often applied to measure A us// and, less frequently, AmpH and AsubH. Many of the reported Asu, // data have been determined with Calvet microcalorimeters (see chapter 9) and from vapor pressure against temperature data obtained with Knudsen cells [35-38]. Reaction-solution calorimetry is the main source of AsinH values. All these auxiliary values are very important because they are frequently required to calculate gas-phase reaction enthalpies and to derive information on the strengths of chemical bonds (see chapter 5)—one of the main goals of molecular energetics. It is thus appropriate to make a brief review of the subject in this introduction. 

Solutions in hand for the reference pairs, it is useful to write out empirical smoothing expressions for the rectilinear densities, reduced density differences, and reduced vapor pressures as functions of Tr and a, following which prediction of reduced liquid densities and vapor pressures is straightforward for systems where Tex and a (equivalently co) are known. If, in addition, the critical property IE s, ln(Tc /Tc), ln(PcVPc), and ln(pcVPc), are available from experiment, theory, or empirical correlation, one can calculate the molar density and vapor pressure IE s for 0.5 < Tr < 1, provided, for VPIE, that Aa/a is known or can be estimated. Thus to calculate liquid density IE s one uses the observed IE on Tc, ln(Tc /Tc), to find (Tr /Tr) at any temperature of interest, and employs the smoothing relations (or numerically solves Equation 13.1) to obtain (pR /pR). Since (MpIE)R = ln(pR /pR) = ln[(p /pc )/(p/pc)] it follows that ln(p7p)(MpIE)R- -ln(pcVpc). For VPIE s one proceeds similarly, substituting reduced temperatures, critical pressures and Aa/a into the smoothing equations to find ln(P /P)RED and thence ln(P /P), since ln(P /P) = I n( Pr /Pr) + In (Pc /Pc)- The approach outlined for molar density IE cannot be used to rationalize the vapor pressure IE without the introduction of isotope dependent system parameters Aa/a. 

To design a supercritical fluid extraction process for the separation of bioactive substances from natural products, a quantitative knowledge of phase equilibria between target biosolutes and solvent is necessary. The solubility of bioactive coumarin and its various derivatives (i.e., hydroxy-, methyl-, and methoxy-derivatives) in SCCO2 were measured at 308.15-328.15 K and 10-30 MPa. Also, the pure physical properties such as normal boiling point, critical constants, acentric factor, molar volume, and standard vapor pressure for coumarin and its derivatives were estimated. By this estimated information, the measured solubilities were quantitatively correlated by an approximate lattice equation of state (Yoo et al., 1997). 

While the 13 hydrocarbon lumps accurately represent the hydrocarbon conversion kinetics, they must be delumped for the deactivation kinetics. In addition, delumping is necessary to estimate many of the product properties and process conditions important to an effective reformer process model. These include H2 consumption, recycle gas H2 purity, and key reformate properties such as octane number and vapor pressure. The following three lump types had to be delumped the C5- kinetic lump into Cl to C5 light gas components, the paraffin kinetic lumps into isoparaffin and n-paraffin components, and the Cg+ kinetic lumps into Cg, C9, C10, and Cn components by molecular type. 

Physical and Chemical Properties. Physical and chemical properties are essential for estimating the partitioning of a chemical in the environment. Many physical and chemical properties are available for isophorone, but most do not have extensive experimental descriptions accompanying the data therefore, an evaluation of the accuracy of the data is difficult. Specifically, measured vapor pressure, K°°, and Henry s Law constant at environmentally significant temperatures would help to remove doubt regarding the accuracy of the estimated data. The data on physical properties form the basis of much of the input requirements for environmental models that predict the behavior of a chemical under specific conditions, including hazardous waste landfills. The data on the chemical properties, on the other hand, can be useful in predicting certain environmental fates of this chemical. 

As an example of this method development procedure, let us consider the case of diphenyl (biphenyl). The physical and chemical properties of diphenyl are given in Figure 2. We estimated the vapor pressure to be 0.05 mm at 25°C (this is equivalent to 70 ppm). 

Hint Use also other compound properties that are available or that can be estimated to perform simple plausibility tests on the experimental vapor pressure and aqueous solubility data of BC at 25°C. 

Grain, C. F., Vapor Pressure . In Handbook of Chemical Property Estimation Methods Environmental Behavior of Organic Compounds, W. J. Lyman, W. F. Reehl and D. H. Rosenblatt, Eds., McGraw-Hill, New York, 1982a, pp. 14-1 -14-20. 

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