Correlation functions macroscopic

The macroscopic correlation function can be expressed as a product of the relaxation functions g z/zj) at all stages of self-similarity of the fractal system considered [47,154] ... 

Figure 31. Semilog plot of the macroscopic correlation function of the 20-pm sample ( ) and the 30-pm sample (A) at the temperature corresponding to percolation. The solid lines correspond to the htting of the experimental data by the KWW relaxation function. (Reproduced with permission from Ref. 2. Copyright 2002, Elsevier Science B.V.)...

Equations (4.4) and (4.S) are reminiscent of each other in the sense that the diffusional behavior of water in the long-time region results from different, randomly explored, environments, each one being characterized by well-defined diffusion coefficients. Therefore, the corresponding macroscopic correlation function turns out to be an average over several molecular environments, the permanence time in each environment and the transition rate from one to another being determined by a well-defined statistical process. 

Group Contribution Methods. It has been shown that many macroscopic physical properties, ie, those derived from experimental measurements of bulk solutions or substances, can be related to specific constituents of individual molecules. These constituents, or functional groups, are usually composed of commonly found combinations of atoms. One procedure for correlating functional groups to a property is as foUows. (/) A set of... 

The low-temperature chemistry evolved from the macroscopic description of a variety of chemical conversions in the condensed phase to microscopic models, merging with the general trend of present-day rate theory to include quantum effects and to work out a consistent quantal description of chemical reactions. Even though for unbound reactant and product states, i.e., for a gas-phase situation, the use of scattering theory allows one to introduce a formally exact concept of the rate constant as expressed via the flux-flux or related correlation functions, the applicability of this formulation to bound potential energy surfaces still remains an open question. 

There are several attractive features of such a mesoscopic description. Because the dynamics is simple, it is both easy and efficient to simulate. The equations of motion are easily written and the techniques of nonequilibriun statistical mechanics can be used to derive macroscopic laws and correlation function expressions for the transport properties. Accurate analytical expressions for the transport coefficient can be derived. The mesoscopic description can be combined with full molecular dynamics in order to describe the properties of solute species, such as polymers or colloids, in solution. Because all of the conservation laws are satisfied, hydrodynamic interactions, which play an important role in the dynamical properties of such systems, are automatically taken into account. 

Discrete-time velocity correlation function, multiparticle collision dynamics, macroscopic laws and transport coefficients, 103-104 Dissipative structures ... 

Chapter 4 deals with the local dynamics of polymer melts and the glass transition. NSE results on the self- and the pair correlation function relating to the primary and secondary relaxation will be discussed. We will show that the macroscopic flow manifests itself on the nearest neighbour scale and relate the secondary relaxations to intrachain dynamics. The question of the spatial heterogeneity of the a-process will be another important issue. NSE observations demonstrate a subhnear diffusion regime underlying the atomic motions during the structural a-relaxation. 

There is an important case which is intermediate between small bounded systems and macroscopic fully extended systems, namely the description of the surface region of a macroscopic metal. The correlation functions which describe density fluctuations in the surface region are extremely anisotropic and of long range, very unlike their counterparts in the bulk, and the thermodynamic limit must be taken with sufficient care. Consider the static structure factor for a large system of N particles contained within a volume Q,... 

Time-dependent correlation functions are now widely used to provide concise statements of the miscroscopic meaning of a variety of experimental results. These connections between microscopically defined time-dependent correlation functions and macroscopic experiments are usually expressed through spectral densities, which are the Fourier transforms of correlation functions. For example, transport coefficients1 of electrical conductivity, diffusion, viscosity, and heat conductivity can be written as spectral densities of appropriate correlation functions. Likewise, spectral line shapes in absorption, Raman light scattering, neutron scattering, and nuclear jmagnetic resonance are related to appropriate microscopic spectral densities.2... 

However, a question arises - could similar approach be applied to chemical reactions At the first stage the general principles of the system s description in terms of the fundamental kinetic equation should be formulated, which incorporates not only macroscopic variables - particle densities, but also their fluctuational characteristics - the correlation functions. A simplified treatment of the fluctuation spectrum, done at the second stage and restricted to the joint correlation functions, leads to the closed set of non-linear integro-differential equations for the order parameter n and the set of joint functions x(r, t). To a full extent such an approach has been realized for the first time by the authors of this book starting from [28], Following an analogy with the gas-liquid systems, we would like to stress that treatment of chemical reactions do not copy that for the condensed state in statistics. The basic equations of these two theories differ considerably in their form and particular techniques used for simplified treatment of the fluctuation spectrum as a rule could not be transferred from one theory to another. 

Therefore, the joint correlation functions Xvjl (a t)> being at least potentially observable, are more a theoretical than an experimental tool for the description of interacting particles in condensed media. Both these joint functions and macroscopic concentrations nv t) determine the lowest level to characterize the spatio-temporal structure of a system. 

The equation for the time development of macroscopic concentrations formally coincides with the law of mass action but with dimensionless reaction rate K(t) = K(t)/ AnDr ) which is, generally speaking, time-dependent and defined by the flux of the dissimilar particles via the recombination sphere of the radius tq, equation (5.1.51). Using dimensionless units n(t) = 4nrln(t), r = t/tq, t = Dt/r, and the condition of the reflection of similar particles upon collisions, equation (5.1.40) (zero flux through origin), we obtain for the joint correlation functions the equations (6.3.2), (6.3.3). Note that we use the dimensionless diffusion coefficients, a = 2k, IDb = 2(1 — k), k = Da/ Da + Dq) entering equation (6.3.2). 

As in previous Chapters, for practical use this infinite set (7.1.1) has to be decoupled by the Kirkwood - or any other superposition approximation, which permits to reduce a problem to the study of closed set of densities pm,m with indices (m + mr) 2. As earlier, this results in several equations for macroscopic concentrations and three joint correlation functions, for similar, X (r,t),X-s r,t), and dissimilar defects Y(r,t). However, unlike the kinetics of the concentration decay discussed in previous Chapters, for processes with particle sources direct use of Kirkwood s superposition approximation gives good results for small dimesionless concentration parameters Uy t) = nu(t)vo < 1 only (vq is d-dimensional sphere s volume, r0 is its radius). The accumulation kinetics predicted has a very simple form [30, 31]... 

Fig. 7.3. The time development of the joint correlation functions for d = 1. Curves 1 to 4 pvot = 10,102,103 and 104 respectively. Full curves are Y(r, t), broken curves are X(r, i)(in the logarithmic inits). Note that the correlation length (f) infinitely increases in time thus indicating macroscopic defect segregation.

The major advantage of the reactive flux method is that it enables one to initiate trajectories at the barrier top. instead of at reactants or products. Computer time is not wasted by waiting for the particle to escape from the well to the barrier. The method is based on the validity of Onsager s regression hypothesis,97 98 which assures that fluctuations about the equilibrium state decay on the average with the same rate as macroscopic deviations from equilibrium. It is sufficient to know the decay rate of equilibrium correlation functions. There isn t any need to determine the decay rate of the macroscopic population as in the previous subsection. 

When successive values of the chain / differ by small fluctuations, which is the case of macroscopic properties obtained from successive configurations generated by molecular simulations, the auto-correlation function follows an exponential decay [38,40,41]... 

An alternative approach to DS study is to examine the dynamic molecular properties of a substance directly in the time domain. In the linear response approximation, the fluctuations of polarization caused by thermal motion are the same as for the macroscopic rearrangements induced by the electric field [27,28], Thus, one can equate the relaxation function < )(t) and the macroscopic dipole correlation function (DCF) V(t) as follows ... 

The experimental macroscopic DCF for PS samples with porous layers of 20 and 30 pm, obtained by inverse Fourier transforms, are shown in Fig. 31. The correlation functions then were fitted by the KWW expression (23) with... 

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