Macroscopic measurements

Fig. 1. The microscopic enlanglemenl slruciure, e.g, at an interface or in the bulk, is related to the measured macroscopic fracture energy G, via the VP theory of breaking connectivity in the embedded plastic zone (EPZ) at the crack tip. The VP theory determines

$Fig. 1. The microscopic enlanglemenl slruciure, e.g, at an interface or in the bulk, is related to the measured macroscopic fracture energy G, via the VP theory of breaking connectivity in the embedded plastic zone (EPZ) at the crack tip. The VP theory determines <r max in the EPZ, which is related to G, via Hutchinson s J-integral theory.$

By tradition, electrochemistry has been considered a branch of physical chemistry devoted to macroscopic models and theories. We measure macroscopic currents, electrodic potentials, consumed charges, conductivities, admittance, etc. All of these take place on a macroscopic scale and are the result of multiple molecular, atomic, or ionic events taking place at the electrode/electrolyte interface. Great efforts are being made by electrochemists to show that in a century where the most brilliant star of physical chemistry has been quantum chemistry, electrodes can be studied at an atomic level and elemental electron transfers measured.1 The problem is that elemental electrochemical steps and their kinetics and structural consequences cannot be extrapolated to macroscopic and industrial events without including the structure of the surface electrode. [Pg.308]

As discussed, the intuitive notion that there should be a connection between the statistics of the free volumes of a fluid and its measurable macroscopic properties has a long history in studies of the liquid state. In fact, it turns out that this connection is precise in the case of the thermodynamics of the single-component hard-sphere fluid. Specifically, Hoover, Ashurst, and Grover77 and Speedy82 have provided independent derivations that predict the relationship between the hard-sphere compressibility factor Z = P/pksT and the geometric properties of its free volumes, as follows ... [Pg.140]

One important way in which they differ is that currents (either ac or dc) at real interfaces are not uniform across the interface. Therefore, a measured macroscopic dc current density i (A cm" ) will not in general be a microscopic current density i on a small part of the interface (say 1 pm by 1 pm) on a rough or non-uniform electrode. In the formation of each interface it is necessary therefore to ensure that the surface is as smooth as is reasonably practicable. In most cases codes of best practice have been evolved and should generally be followed unless radical improvements are possible. In this way results should at least be comparable from one laboratory to another. [Pg.287]

Note that the terms macroscopic and microscopic constants do not imply that these quantities measure macroscopic or microscopic quantities, respectively. Here, in the macroscopic view we have simply grouped the two microscopic species (0, 1) and (1, 0) into one species denoted by (1). Both of these constants can be macroscopic or microscopic, depending on whether we study the binding per molecule or per one mole of molecules. [Pg.115]

List some reasons why it is desirable to relate Hamaker constants to measurable macroscopic properties instead of relying entirely on molecular parameters. [Pg.495]

At the beginning of the analysis, the ensemble of frequencies is incoherent and has no measurable macroscopic effect on the cell. Ions with the same m/z ratio must be made coherent to conduct a frequency analysis. This is achieved by irradiating the cell with a short radiofrequency pulse (ca. 1 ms lifetime) that includes all the frequencies to be determined. During the irradiation pulse, ions will increase their... [Pg.300]

Experimental justification for specification of the angle at the point of three-phase contact comes from the results of Surek and Chalmers (139), which verify that a particular value of < )0 measured macroscopically can be associated with the crystal growth of a material in a specific crystallographic orientation and that < >o is roughly independent of growth rate. [Pg.94]

Section 5.1 presents the fundamental method as the heart of the chapter— the statistical thermodynamics approach to hydrate phase equilibria. The basic statistical thermodynamic equations are developed, and relationships to measurable, macroscopic hydrate properties are given. The parameters for the method are determined from both macroscopic (e.g., temperature and pressure) and microscopic (spectroscopic, diffraction) measurements. A Gibbs free energy calculation algorithm is given for multicomponent, multiphase systems for comparison with the methods described in Chapter 4. Finally, Section 5.1 concludes with ab initio modifications to the method, along with an assessment of method accuracy. [Pg.257]

In addition to the change in the theoretical methods applied to hydrates, there have been significant advancements and widespread use of meso- and microscopic tools in hydrate research. Conversely, the typical static experimental apparatus used today to measure macroscopic properties, such as phase equilibria properties, is based on the same principles as the apparatus used by Deaton and Frost (1946). In part, this is due to the fact that the simplest apparatus is both the most elegant and reliable simulation of hydrate formation in industrial systems. In Section 6.1.1 apparatuses for the determination of hydrate thermodynamic and transport macroscopic properties are reviewed. [Pg.319]

The experimental apparatuses for hydrate phase equilibria underwent considerable evolution during the nineteenth century. During the last half century the standard methods for measuring macroscopic equilibria have not changed considerably. Table 6.1 summarizes the different macroscopic experimental methods used to study hydrate properties. [Pg.320]

The application of thermodynamics to any real problem starts with the identification of a particular body of matter as the focus of attention. This quantity of matter is called the system, and its thermodynamic state is defined by a few measurable macroscopic properties. These depend on the fundamental dimensions of science, of which length, time, mass, temperature, and amount of substance are of interest here. [Pg.9]

A prediction theory consists of a set of equations that describes some of the measurable macroscopic properties in terms of the microscopic properties of the model system. [Pg.352]

The first problem is concerned with the definitions of the quantities calculated and measured. It has only gradually emerged over the last decades that there was considerable ambiguity about the definition of some of the reported parameters. In 1992 Willetts et al (referred to as WRBS) gave a detailed account of the various conventions that have been applied by different authors in defining the molecular response functions, but more recently Reiss has suggested that there are still inconsistencies in the way that the experimentally measured, macroscopic, response functions are reported. [Pg.248]

Eqns (7.16), (7.24) and (7.25) can be applied easily to available measured macroscopic quantities and have been used in many of the reported analyses of EFISH data. There remains the question of whether the neglect of the other terms in eqn (7.21) is justified and whether a proper assessment of the parameter, n is required. [Pg.264]

The present paper is devoted to the local composition of liquid mixtures calculated in the framework of the Kirkwood—Buff theory of solutions. A new method is suggested to calculate the excess (or deficit) number of various molecules around a selected (central) molecule in binary and multicomponent liquid mixtures in terms of measurable macroscopic thermodynamic quantities, such as the derivatives of the chemical potentials with respect to concentrations, the isothermal compressibility, and the partial molar volumes. This method accounts for an inaccessible volume due to the presence of a central molecule and is applied to binary and ternary mixtures. For the ideal binary mixture it is shown that because of the difference in the volumes of the pure components there is an excess (or deficit) number of different molecules around a central molecule. The excess (or deficit) becomes zero when the components of the ideal binary mixture have the same volume. The new method is also applied to methanol + water and 2-propanol -I- water mixtures. In the case of the 2-propanol + water mixture, the new method, in contrast to the other ones, indicates that clusters dominated by 2-propanol disappear at high alcohol mole fractions, in agreement with experimental observations. Finally, it is shown that the application of the new procedure to the ternary mixture water/protein/cosolvent at infinite dilution of the protein led to almost the same results as the methods involving a reference state. [Pg.52]

The Kirkwood—Buff (KB) theory of solution (often called fluctuation theory) employs the grand canonical ensemble to relate macroscopic properties, such as the derivatives of the chemical potentials with respect to concentrations, the isothermal compressibility, and the partial molar volnmes, to microscopic properties in the form of spatial integrals involving the radial distribution function. This theory allows one to obtain information regarding some microscopic characteristics of mnlti-component mixtures from measurable macroscopic thermodynamic quantities. However, despite its attractiveness, the KB theory was rarely used in the first three decades after its publication for two main reasons (1) the lack of precise data (in particular regarding the composition dependence of the chemical potentials) and (2) the difficulty to interpret the results obtained. Only after Ben-Naim indicated how to calculate numerically the Kirkwood—Buff integrals (KBIs) for binary systems was this theory used more frequently. [Pg.52]

One of the most important applications of the KB theory consists of its use to extract some microscopic characteristics of liquid mixtures from measurable macroscopic thermodynamic quantities. The excess (or deficit) number of molecules of... [Pg.57]

Answers to such difficult questions can be found in applied thermodynamics - in terms of measured, macroscopic values of pressures, temperatures, compositions, volumes, enthalpies, etc. This chapter provides an overview of natural gas clathrate hydrates - structures, phase diagrams, and thermodynamic predictions/measurements that guide our understanding in dealing with such questions. The hydrate historical perspective provides an example of how knowledge advances in a technical field. At the conclusion of the chapter, future thermodynamic challenges are presented. [Pg.58]

This section defines the entropy function in terms of measurable macroscopic quantities to provide a basis for calculating changes in entropy for specific processes. The definition is part of the second law of thermodynamics, which is... [Pg.537]

Internal energy. Internal energy (J/) is a macroscopic measure of the molecular, atomic, and subatomic energies, all of which follow definite microscopic conservation rules for dynamic systems. Because no instruments exist with which to measure internal energy directly on a macroscopic scale, internal energy must be calculated from certain other variables that can be measured macroscopically, such as pressure, volume, temperature, and composition. [Pg.371]

Here comes the important point The variations of measured macroscopic molecular properties can reasonably be assumed to be reflections of variations of the intrinsic properties at the molecular level. Descriptors which depend on the same molecular property are most likely to be correlated to each other. The principal components describe the systematic variation of the descriptors over the set of compounds. Descriptors which are correlated to each other will be described by the same principal component. The principal component vectors are mutually orthogonal, and different component will therefore describe independent and uncorrelated variations of the descriptors. Hence, different components will portray a variation in the data due to different intrinsic properties. These intrinsic properties, which manifest themselves as a variation of the macroscopic descriptors, are called the principal properties.[3]... [Pg.348]

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