Properties, estimation

it is important to know not only the property itself at a standard temperature but also its temperature dependence. Temperature functions are available for a wealth of fluid compounds, such as solvents. However, these functions are compound specific. For limited sets of compounds, functions have been developed that describe properties as a function of both molecular structure and temperature (Section 1.9). 

Computer-Aided Property Estimation Computer-aided structure estimation requires the structure of the chemical compounds to be encoded in a computer-readable language. Computers most efficiently process linear strings of data, and hence linear notation systems were developed for chemical structure representation. Several such systems have been described in the literature. SMILES, the Simplified Molecular Input Line Entry System, by Weininger and collaborators [2-4], has found wide acceptance and is being used in the Toolkit. Here, only a brief summary of SMILES rules is given. A more detailed description, together with a tutorial and examples, is given in Appendix A. 

SMILES is based on die natural grammer of atomic symbols and symbols for bonds. The most important rules are as follows  

Atoms in aromatic rings are specified by lowercase letters. For example, the nitrogen in an amino acid is represented as N, the nitrogen in pyridin by n, and carbon in benzene by c. 

Single, double, triple, and aromatic bonds are represented by the symbols -, =,, and , respectively. Single and aromatic bonds may be omitted. 

Each of the property information systems has an extensive set of subroutines to determine the parameters for vapor pressure equations (e.g., the extended Antoine equation), heat capacity equations, etc., by regression and to estimate the thehnophysical and transport properties. The latter subroutines are called to determine the state of a chemical mixture (phases at equilibrium) and its properties (density, enthalpy, entropy, etc.) When calculating phase equilibria, the fugacities of the species are needed for each of the phases. A review of the phase equilibrium equations, as well as the facilities provided by the process simulators for the calculation of phase equilibria, is provided on the CD-ROM that accompanies this book (see ASPEN- Physical Property Estimation and HYSYS Physical Property Estimation). 

As mentioned above, when a data record for a pure species cannot be located in one of its data banks, each of the property information systems permits the designer to enter the missing constants and parameters. Furthermore, methods are provided to estimate the constants and parameters when the designer cannot provide these. This is especially important when laboratory and pilot-plant data are not available. 

Usually, bond- or group-contribution methods are used to estimate the constants and parameters for pure species, with the designer providing the molecular structure of the chemical species, as shown, for example, for trifluoropropylene  

all atoms, with the exception of hydrogen, are numbered and the bonds associated with each carbon atom and its adjacent numbered atoms can be specified as follows  

Number Type Number Type Bond Type 

This last section provides information that will allow the practitioner to estimate key physical and chemical properties of materials. Although the scientific community has traditionally resorted to experimental methods to accurately determine the aforementioned properties, that option may very well not be available when dealing with new materials. 

Predictive methods, albeit traditional ones, may be the only option available to obtain a first estimate of these properties. It should be noted that significant errors may be involved since extrapolating (or extending) satisfactory estimation procedures at the macroscale level may not always be reasonable. Notwithstanding these concerns, procedures to estimate some of the key physical and chemical properties in chemical kinetics given below are available in the literature.  

References (3,4) arc somewhat complementary, but each provides extensive information on this topic. This includes equations and procedures on several other properties not listed above. The interested reader should check these references for more details. 

Is property estimation important Absolutely. As indicated above, there are times and situations when experimental procedures cannot be implemented. For this scenario, one can turn to theoretical and semitheoretical methods and equations to obtain first estimates of important property information for some reactor studies. 

One could argue that the present procedures available to estimate the properties of materials are based on questionable approaches. Nonetheless, the traditional methods available for property estimation either may be applicable or may suggest alternative theoretical approaches. 

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E. J. Baum, Chemical Property Estimation Theory and Applications Lewis, Boca Raton (1998). 

W. J. Lyman, W. F. Reehl, D. H. Rosenblatt, Handbook of Chemical Property Estimation Methods American Chemical Society, Washington (1990). 

Equations-Oriented Simulators. In contrast to the sequential-modular simulators that handle the calculations of each unit operation as an iaput—output module, the equations-oriented simulators treat all the material and energy balance equations that arise ia all the unit operations of the process dow sheet as one set of simultaneous equations. In some cases, the physical properties estimation equations also are iacluded as additional equations ia this set of simultaneous equations. 

General Properties of Computerized Physical Property System. Flow-sheeting calculations tend to have voracious appetites for physical property estimations. To model a distillation column one may request estimates for chemical potential (or fugacity) and for enthalpies 10,000 or more times. Depending on the complexity of the property methods used, these calculations could represent 80% or more of the computer time requited to do a simulation. The design of the physical property estimation system must therefore be done with extreme care. 

Numerous other methods have been used to predict properties of gases and Hquids. These include group contribution, reference substance, approaches, and many others. However, corresponding states theory has been one of the most thoroughly investigated methods and has become an important basis for the development of correlation and property estimation techniques. The methods derived from the corresponding states theory for Hquid and gas property estimation have proved invaluable for work such as process and equipment design. 

Critica.1 Properties. Several methods have been developed to estimate critical pressure, temperature, and volume, U). Many other properties can be estimated from these properties. Error propagation can be large for physical property estimations based on critical properties from group contribution methods. Thus sensitivity analyses are recommended. The Ambrose method (185) was found to be more accurate (186) than the Lyderson (187) method, although it is computationally more complex. The Joback and Reid method (188) is only slightly less accurate overall than the Ambrose method, and is more accurate for some specific substances. Other methods of lesser overall accuracy are also available (189,190) (T, (191,192) (T, P ),... 

Heat Capacity. The multiple property estimation methods for constant pressure ideal-gas heat capacities cover a broad range of organic compounds (188,216,217). Joback s method (188) is the easiest to use however, usage of all these methods has been recommended only over the range 280—1100 K (7). An accurate method for ideal-gas heat capacities (constant pressure), limited to hydrocarbons, has been presented (218) that involves a fit of seven variables, and includes steric, ring, branching, alkene, and even allene corrections. 

Hctivity Coefficients. Most activity coefficient property estimation methods are generally appHcable only to pure substances. Methods for properties of multicomponent systems are more complex and parameter fits usually rely on less experimental data. The primary group contribution methods of activity coefficient estimation are ASOG and UNIEAC. Of the two, UNIEAC has been fit to more combinations of groups and therefore can be appHed to a wider variety of compounds. Both methods are restricted to organic compounds and water. 

LymanWJ. 1990. Adsorption coefficient for soils and sediment. In Handbook of chemical property estimation methods. Environmental behavior of organic compounds. Lyman WJ, Reehl WE, Rosenblatt DH, eds. Washington, DC American Chemical Society. ... 

Conventionally, the sample is initially saturated with one fluid phase, perhaps including the other phase at the irreducible saturation. The second fluid phase is injected at a constant flow rate. The pressure drop and cumulative production are measured. A relatively high flow velocity is used to try to negate capillary pressure effects, so as to simplify the associated estimation problem. However, as relative permeability functions depend on capillary number, these functions should be determined under the conditions characteristic of reservoir or aquifer conditions [33]. Under these conditions, capillary pressure effects are important, and should be included within the mathematical model of the experiment used to obtain property estimates. 

Group contribution techniques are based on the concept that a particular physical property of a compound can be considered to be made up of contributions from the constituent atoms, groups, and bonds the contributions being determined from experimental data. They provide the designer with simple, convenient, methods for physical property estimation requiring only a knowledge of the structural formula of the compound. 

Lyman WJ, Reehl WF, Rosenblatt DH. 1982. Handbook of Chemical Property Estimation Methods Environmental behavior of organic compounds. New York McGraw-Hill Book Company, 1-1 to 1-2. 

Horvath, A. L., Handbook of Aqueous Electrolyte Solutions, Physical Properties, Estimation and Correlation Methods, Ellis Horwood, Chichester, 1985. 

Scow, K.M., Rate of biodegradation, in Handbook of Chemical Property Estimation Methods Environmental Behavior of Organic Compounds, Lyman, W. J., Reehl, W.F., and Rosenblatt, D.H., Eds., McGraw-Hill, New York, 1982, pp. 9-1-9-85. 

Lyman, W. et al. (1982). Chemical property estimation methods. McGraw-Hill Book Company, New York, NY. 

We have developed a two-step procedure for in silico screening of compound libraries based on biopharmaceutical property estimation linked to a mechanistic... 

Boethling RS, Mackay D (2000) Handbook of property estimation methods for chemicals environmental and health science. Lewis Publishers, Boca Raton London New York Washington D.C. 

Boethling, R.S., Mackay, D. Eds. (2000) Handbook of Property Estimation Methods Environmental and Health Sciences. CRC Press, Boca Raton, FL. 

Thermodynamic data (enthalpy of reaction, specific heat, thermal conductivity) for simple systems can frequently be found in date bases. Such data can also be determined by physical property estimation procedures and experimental methods. The latter is the only choice for complex multicomponent systems. 

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