Review of Classical Statistical Mechanics

This section summarizes the classical, equilibrium, statistical mechanics of many-particle systems, where the particles are described by their positions, q, and momenta, p. The section begins with a review of the definition of entropy and a derivation of the Boltzmann distribution and discusses the effects of fluctuations about the most probable state of a system. Some worked examples are presented to illustrate the thermodynamics of the nearly ideal gas and the Gaussian probability distribution for fluctuations. 

The key ingredient in a statistical description of classical, many-particle systems where each particle labeled by i is described by its momentum, pi, and position, 9, is the probability distribution function, P pi,qi ). This distribution is a function of the momenta and positions of each particle and is taken to be normalized to unity — i.e., the sum of the probabilities of finding a particle with all possible momenta and positions is unity  

The entropy, 5, is defined by the negative of the average value of the logarithm of P [pi, qi ) and is a measure of the number of states that are available to the system  

In thermal equilibrium, the most probable distribution is the one that maximizes the entropy, subject to any constraints that may act on the system. These results are easily generalized to systems where the degrees of freedom are not necessarily those of position and momentum — e.g., two-state systems. For simplicity, in the following discussion, we consider position and momentum. Also for simplicity, we drop the index i and consider the vectors p and q to denote the positions and momenta of all of the particles e-g P = iPx,u Py,u Pz,u Px,2 Py,2 Pz,2-.), where 1,2... are the labels of the individual particles. 

For a system with a single particle in three spatial dimensions, the partition function, Z, is defined by 

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In this chapter, we begin with some remarks on the technological and scientific importance of complex materials and interfaces and motivate the study of interface and surface properties. We then review some of the physical and mathematical methods that are used in the subsequent discussions of interface and membrane statistical thermodynamics. Many of these topics are discussed more fully in the references and throughout this chapter. We begin with a review of classical statistical mechanics ", including a description of fluctuations about equilibrium and of binary mixtures. The mathematical description of an interface is then presented (using only vector calculus) and the calculation of the area and curvature of an interface wifli an arbitrary shape is demonstrated. Finally, the chapter is concluded by a brief summary of hydrodynamics. ... 

The evaluation of the free energy is essential to quantitatively treat a chemical process in condensed phase. In this section, we review methods of free-energy calculation within the context of classical statistical mechanics. We start with the standard free-energy perturbation and thermodynamic integration methods. We then introduce the method of distribution functions in solution. The method of energy representation is described in its classical form in this section, and is combined with the QM/MM methodology in the next section. 

In conclusion, the condition of ordinary statistical physics makes the decoherence theory a valuable perspective, as well as an attractive way of deriving classical from quantum physics. The argument that the Markov approximation itself is subtly related to introducing ingredients that are foreign to quantum mechanics [23] cannot convince the advocates of decoherence theory to abandon the certainties of quantum theory for the uncertainties for a search for a new physics. The only possible way of converting a philosophical debate into a scientific issue, as suggested by the results that we have concisely reviewed in this section, is to study the conditions of anomalous statistical mechanics. In the next sections we shall explore with more attention these conditions. 

Phase transitions in statistical mechanical calculations arise only in the thermodynamic limit, in which the volume of the system and the number of particles go to infinity with fixed density. Only in this limit the free energy, or any thermodynamic quantity, is a singular function of the temperature or external fields. However, real experimental systems are finite and certainly exhibit phase transitions marked by apparently singular thermodynamic quantities. Finite-size scaling (FSS), which was formulated by Fisher [22] in 1971 and further developed by a number of authors (see Refs. 23-25 and references therein), has been used in order to extrapolate the information available from a finite system to the thermodynamic limit. Finite-size scaling in classical statistical mechanics has been reviewed in a number of excellent review chapters [22-24] and is not the subject of this review chapter. 

The time-dependent classical statistical mechanics of systems of simple molecules is reviewed. The Liouville equation is derived the relationship between the generalized susceptibility and time-correlation function of molecular variables is obtained and a derivation of the generalized Langevin equation from the Liouville equation is given. The G.L.E. is then simplified and/or approximated by introducing physical assumptions that are appropriate to the problem of rotational motion in a dense fluid. Finally, the well-known expressions for spectral intensity of infrared and Raman vibration-rotation bands are reformulated in terms of time correlation functions. As an illustration, a brief discussion of the application of these results to the analysis of spectral data for liquid benzene is presented. 

Our rather modest goal is to obtain some general formulas and to show how classical and quantum statistical mechanics are related to each other. We will make some elementary comments on the application to nonideal gases and liquids. More detailed discussions are found in the statistical mechanics textbooks listed at the end of this book. Many research articles in classical statistical mechanics appear in journals sueh as The Journal of Chemical Physics, The Journal of Physical Chemistry, The Physical Review, and Physica. 

In the remainder of this chapter, we review the fundamentals that underlie the theoretical developments in this book. We outline, in sequence, the concept of density of states and partition function, the most basic approaches to calculating free energies and the essential strategies for improving the efficiency of these calculations. The ideas discussed here are, most likely, known to the reader. They can also be found in classical books on statistical mechanics [132-134] and molecular simulations [135, 136]. Thus, we do not attempt to be exhaustive. On the contrary, we present the material in a way that is most directly relevant to the topics covered in the book. 

Here, we review an adiabatic approximation for the statistical mechanics of a stiff quantum mechanical system, in which vibrations of the hard coordinates are first treated quantum mechanically, while treating the more slowly evolving soft coordinates and momenta for this purpose as parameters, and in which the constrained free energy obtained by summing over vibrational quantum states is then used as a potential energy in a classical treatment of the soft coordinates and momenta. 

In this chapter we will mostly focus on the application of molecular dynamics simulation technique to understand solvation process in polymers. The organization of this chapter is as follow. In the first few sections the thermodynamics and statistical mechanics of solvation are introduced. In this regards, Flory s theory of polymer solutions has been compared with the classical solution methods for interpretation of experimental data. Very dilute solution of gases in polymers and the methods of calculation of chemical potentials, and hence calculation of Henry s law constants and sorption isotherms of gases in polymers are discussed in Section 11.6.1. The solution of polymers in solvents, solvent effect on equilibrium and dynamics of polymer-size change in solutions, and the solvation structures are described, with the main emphasis on molecular dynamics simulation method to obtain understanding of solvation of nonpolar polymers in nonpolar solvents and that of polar polymers in polar solvents, in Section 11.6.2. Finally, the dynamics of solvation with a short review of the experimental, theoretical, and simulation methods are explained in Section 11.7. 

Elementary processes in chemical dynamics are universally important, besides their own virtues, in that they can link statistical mechanics to deterministic dynamics based on quantum and classical mechanics. The linear surprisal is one of the most outstanding discoveries in this aspect (we only refer to review articles [2-7]), the theoretical foundation of which is not yet well established. In view of our findings in the previous section, it is worth studying a possible origin of the linear surprisal theory in terms of variational statistical theory for microcanonical ensemble. 

One of the most active areas of research in the statistical mechanics of interfacial systems in recent years has been the problem of freezing. The principal source of progress in this field has been the application of the classical density-functional theories (for a review of the fundamentals in these methods, see, for example, Evans ). For atomic fluids, such apphcations were pioneered by Ramakrishnan and Yussouff and subsequently by Haymet and Oxtoby and others (see, for example, Baret et al. ). Of course, such theories can also be applied to the vapor-liquid interface as well as to problems such as phase transitions in liquid crystals. Density-functional theories for these latter systems have not so far involved use of interaction site models for the intermolecular forces. 

In classical mechanics It Is assumed that at each Instant of time a particle is at a definite position x. Review of experiments, however, reveals that each of many measurements of position of Identical particles in identical conditions does not yield the same result. In addition, and more importantly, the result of each measurement is unpredictable. Similar remarks can be made about measurement results of properties, such as energy and momentum, of any system. Close scrutiny of the experimental evidence has ruled out the possibility that the unpredictability of microscopic measurement results are due to either inaccuracies in the prescription of initial conditions or errors in measurement. As a result, it has been concluded that this unpredictability reflects objective characteristics inherent to the nature of matter, and that it can be described only by quantum theory. In this theory, measurement results are predicted probabilistically, namely, with ranges of values and a probability distribution over each range. In constrast to statistics, each set of probabilities of quantum mechanics is associated with a state of matter, including a state of a single particle, and not with a model that describes ignorance or faulty experimentation. 

Tribus, Myron Evans, Robert B. A Minimum Statistical Mechanics from Which Classical Thermostatics May Be Derived, in the book, "A Critical Review of Thermodynamics," Mono Book Co., Baltimore, MD, 1970. 

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