Property estimation methods classes

Classes of Estimation Methods Table 1.1.1 summarizes the property estimation methods considered in this book. Quantitative property-property relationships (QPPRs) are defined as mathematical relationships that relate the query property to one or several properties. QPPRs are derived theoretically using physicochemical principles or empirically using experimental data and statistical techniques. By contrast, quantitative structure-property relationships (QSPRs) relate the molecular structure to numerical values indicating physicochemical properties. Since the molecular structure is an inherently qualitative attribute, structural information has first to be expressed as a numerical values, termed molecular descriptors or indicators before correlations can be evaluated. Molecular descriptors are derived from the compound structure (i.e., the molecular graph), using structural information, fundamental or empirical physicochemical constants and relationships, and stereochemcial principles. The molecular mass is an example of a molecular descriptor. It is derived from the molecular structure and the atomic masses of the atoms contained in the molecule. An important chemical principle involved in property estimation is structural similarity. The fundamental notion is that the property of a compound depends on its structure and that similar chemical stuctures (similarity appropriately defined) behave similarly in similar environments. 

Physical property estimation methods may be classified into six general areas (1) theory and empirical extension of theory, (2) corresponding states, (3) group contributions, (4) computational chemistry, (5) empirical and quantitative structure property relations (QSPR) correlations, and (6) molecular simulation. A quick overview of each class is given below to provide context for the methods and to define the general assumptions, accuracies, and limitations inherent in each. 

The Need for Estimation Methods 1-1.1 Regulatory Context 1-1.2 Chemical Design 1-2 Overview of this Work 1-2.1 Chapter Contents 1-2.2 Properties of Pure Substances 1-2.3 Partitioning Properties 1-2.4 Reactivity or Persistence 1-2.5 Specific Classes of Substances 1-2.6 Benchmark Chemicals References... 

The PMN review process has evolved over time within the constraints set by TSCA. An important constraint is that submitters are required to furnish only test data already in their possession (if any) and are not required to conduct a battery of tests as a precondition for approval. This generalization holds true for basic chemical property data as well as toxicity data, and it is the main reason why TSCA has been such a powerful impetus for developing estimation methods for many of the parameters needed in environmental assessment. To illustrate how extreme the situation is, in one study of more than 8,000 PMNs for class 1 chemical substances (i.e., those for which a specific chemical structure can be drawn) that were received from 1979 through 1990,Lynch et al. (1991) found only 300 that contained any of the property data noted earlier as needed for environmental assessment. The U.S. is unique among industrialized nations in requiring its assessors to work in the virtual absence of test data. 

As in Lyman s Handbook, emphasis is on broadly applicable estimation methods. Given the many and varied reasons that one might be interested in chemical property estimation, we believe that most users of this book will have less interest in chemical class-specific estimation methods. Obviously such methods are reliable only for that class, which may be defined very narrowly, and they may produce substantial yet unknown error if applied to compounds that differ significantly. Many of the newer methods were developed using much larger and more varied training sets, thus are more likely to be useful for diverse and/or structurally complex compounds. Therefore, in contrast to the situation that existed in 1982 when Lyman s Handbook was published, current users often do not need to make decisions about which of several class-specific methods seems most applicable to the compound of interest. 

However, methods for predicting environmentally relevant properties of surfactants applicable for all surfactant classes are presently not available. Due to the absence of validated estimation methods, this chapter s goal is to supply information necessary to understanding the behavior of surfactants in the environment and to provide data on the relevant properties of surfactants. 

Methods for the following general classes of properties are presented here basic properties, thermodynamic properties, reaction properties, and transport properties, but the treatment is restricted in each class to properties of direct relevance to our subject. Also included is a short section on estimating the velocity of ultrasound in single and mixed liquid media because of its importance in a subsequent chapter. It must be emphasized that, wherever possible, reported experimental values should be used because estimation methods can never be as precise. 

The importance of the penicillins as a class of heterocyclic compounds derives primarily from their effectiveness in the treatment of bacterial infections in mammals (especially humans). It has been estimated that, in 1980, the worldwide production of antibiotics was 25 000 tons and, of this, approximately 17 000 tons were penicillins (81MI51103). The Food and Drug Administration has estimated that, in 1979 in the U.S.A., 30.1 x 10 prescriptions of penicillin V and 44.3 x 10 prescriptions of ampicillin/amoxicillin were dispensed. This level of usage indicates that, compared to other methods of dealing with bacterial infection, the cost-benefit properties of penicillin therapy are particularly favorable. Stated differently, penicillin treatment leads to the elimination of the pathogen in a relatively high percentage of cases of bacterial infection at a relatively low cost to the patient in terms of toxic reactions and financial resources. 

In summary, bond and group additivity rules, as well as the model compound approach, in conjunction with statistical mechanics, represent useful tools for the estimation of thermochemical properties. However, their utility for the determination of thermochemistry of new classes of compounds is limited, especially with regard to the determination of Aiff. For new classes of compounds, we must resort to experiments, as well as to computational quantum mechanical methods. 

Thermodynamic property values can also be estimated for many classes of compound in the gaseous state with a precision approaching that of experimental measurement. Various methods are outlined in ref. 9, but the best currently available is almost certainly that due to Benson. This is a group contribution method applicable to and Cp at... 

Class II Methods. The methods of Class II are those that use the simultaneous Newton-Raphson approach, in which all the equations are linearized by a first order Taylor series expansion about some estimate of the primitive variables. In its most general form, this expansion includes terms arising from the dependence of the thermo-physical property models on the primitive variables. The resulting system of linear equations is solved for a set of iteration variable corrections, which are then applied to obtain a new estimate. This procedure is repeated until the magnitudes of the corrections are sufficiently small. 

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