Empirical property

When trying to understand and to manipulate matter and materials, chemistry does not start by looking at the natural world in all its complexity. Rather, it seeks to establish what have been termed exemplar phenomena ideal or simplified examples that are capable of investigation with the tools available at the time (Gilbert, Borrlter, Elmer, 2000). This level consists of representatiorrs of the empirical properties of solids, liquids (taken to include solutions, especially aqueous solutiorts), colloids, gases and aerosols. These properties are perceptible in chemistry laboratories and in everyday life and are therefore able to be meastrred. Examples of such properties are mass, density, concentration, pH, temperatrrre and osmotic presstrre. 

In contrast, the NBO and NRT methods make no use of molecular geometry information (experimental or theoretical), but instead provide optimal descriptions of orbital composition or electron-density distributions based directly on the first-order density operator. For this reason the NBO/NRT indices have predictive utility for a broad range of chemical phenomena, without bias toward geometry or other particular empirical properties. 

Therefore, we have shown that thermodynamic principles and properties can be used to describe combustion reactions provided their stoichiometry is known. Since measurements in fire are based on the fuel mass lost, yields are used as empirical properties to describe the reaction and its products. When fire conditions become ventilation-limited ((/> > 1), the yield properties of a given fuel depend on general trends are accepted. 

Equation [1] relates a (macroscopic) bulk, empirical property, Y, with some set, X, of (microscopic) molecular structural parameters (descriptors). The equation as shown is linear in that each term involves a first power for its descriptor. Fligher order descriptors may also be used. The coefficients, Uj, are obtained with the aid of statistical methods, particularly, regression... 

The kinetic consideration outlined here is very similarly based on empirical properties of metal ions which (although loosely) correspond to their a-and TT-bonding capacities and - directions like with Hammett s approach (Hammett 1973 Schiiiirmann 1991) for reaction kinetics in benzenoid aromatics. In either case, there is no precise link as yet with electronic parameters closely defined in quantum chemistry like charge density, as the principal objective by now is to understand reactions kinetics and thus selection of certain catalysts, discriminating against others. 

Figure 2 represents an empirical property as a function a C -> R which maps the set C of chemicals into the real line R. A nonempirical QSAR may be regarded as a composition of a description function, PpC D, mapping each chemical structure of C into a space of nonempirical structural descriptors (D) and a prediction function, P2. D R, which maps the descriptors into the real line. When [a(C) - P2Pi(C)] is within the range of experimental errors, we say that we have a good nonempirical... 

Because they are empirical properties, Marshall stability and flow cannot be used in analytical pavement design calculations. 

At the target mixture, the following empirical properties should be determined drainage capacity, water sensitivity, particle loss and binder drainage. 

At the target composition, the following empirical properties should be determined (a) indentation (resistance to permanent deformation) and, when required, (b) resistance to abrasion by studded tyres, (c) resistance to fuel for application on airfields and (d) resistance to de-icing fluid for application on airfields. 

The methodology is based on volumetric and empirical properties of DGCAs. It has been presented in conferences (Nikolaides 1992, 1993) and has been accepted for use in Greece (MPW D14 1994) and Indonesia (Indonesian MPW 1990). 

Experimentally, activities are measured relative to the empirical properties of the end-member oxide so that by definition aMO = 1 0 in pure liquid MO. The binary titration curves used to fit values of K are therefore each normalized to a value of 1.0 for aj Q when 1 0. However in this standard state, values of Xg2- f or different oxides may be quite different. 

From a fundamental point of view there are therefore a number of difficulties. There is no satisfactory theory that accounts for all observations on electrophoretic deposition. It is desirable to find suitable physical/chemical parameters that characterise a suspension sufficiently in order that its ability to deposit can be predicted. Most investigators use zeta potential or electrophoretic mobility, but these do not uniquely determine the ability of a suspension to deposit. For example, in suspensions of aluminium in alcohol the addition of an electrolyte C2ujses no significant change to the zeta potential, but deposits can only be obtained in the presence of the electrolyte The stability of the suspension is evidently its most significant property, but this is a somewhat empirical property not closely related to fundamental parameters. 

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