Self-diffusion coefficient viscosity correlation

Self-diffusivity, cooperatively with ionic conductivity, provides a coherent account of ionicity of ionic liquids. The PGSE-NMR method has been found to be a convenient means to independently measure the self-diffusion coefficients of the anions and the cations in the ionic liquids. Temperature dependencies of the self-diffusion coefficient, viscosity and ionic conductivity for the ionic liquids, cannot be explained simply by Arrhenius equation rather, they follow the VFT equation. There is a simple correlation of the summation of the cationic and the anionic diffusion coefficients for each ionic liquid with the inverse of the viscosity. The apparent cationic transference number in ionic liquids has also been found to have dependence on the... 

Many physical properties undergo dramatic changes in value as water is heated and pressurized from sub- to supercritical conditions, particularly in the region of the critical point where some properties such as heat capacity reach a singularity. This change in behavior means that more familiar correlations of properties measured at subcritical conditions are likely to be inaccurate when applied at supercritical conditions. There have been some experimental studies performed to measure, tabulate, and in some cases correlate values of key properties of supercritical water, such as the self-diffusion coefficient, viscosity,thermal conductivity," heat capacity at constant volume," dielectric constant," and selfdissociation constant." " Far more work has been devoted to calculation of property values from models fitted empirically to data or developed more rigorously through molecular simulation. For PVT data and its derivatives, several attempts... 

On the other hand, we have, for non-equilibrium dynamic property, the time correlation function TCF, which is dynamic counterpart to g(r). One can define various TCP s for each purpose. However, at the present stage, no extensive theoretical relation has been derived between TCF and ([(r). Therefore, direct determination of self-diffusion coefficient, viscosity coefficient by the molecular simulation gives significant contribution in dynamics studies. 

Basic requirements on feasible systems and approaches for computational modeling of fuel cell materials are (i) the computational approach must be consistent with fundamental physical principles, that is, it must obey the laws of thermodynamics, statistical mechanics, electrodynamics, classical mechanics, and quantum mechanics (ii) the structural model must provide a sufficiently detailed representation of the real system it must include the appropriate set of species and represent the composition of interest, specified in terms of mass or volume fractions of components (iii) asymptotic limits, corresponding to uniform and pure phases of system components, as well as basic thermodynamic and kinetic properties must be reproduced, for example, density, viscosity, dielectric properties, self-diffusion coefficients, and correlation functions (iv) the simulation must be able to treat systems of sufficient size and simulation time in order to provide meaningful results for properties of interest and (v) the main results of a simulation must be consistent with experimental findings on structure and transport properties. 

Figure 2. A pictorial representation of the mode coupling theory scheme for the calculation of the time-dependent friction (f) on a tagged molecule at time t. The rest of the notation is as follows Fs(q,t), self-scattering function F(q,t), intermediate scattering function D, self-diffusion coefficient t]s(t), time-dependnet shear viscosity Cu(q,t), longitudinal current correlation function C q,t), longitudinal current correlation functioa...

The practical advantage of these relations is that, in MD simulations, single molecule properties like the self-diffusion coefficient and rotational relaxation times converge much faster than system properties due to additional averaging over the number of molecules in the ensemble. We applied eqs. 10 and 11 to our MD results using data at 800 K as a reference point in order to predict the viscosity over the entire temperature interval. In Fig. 7 we compare the predicted values with those obtained from simulation. It appears that in the temperature interval 600 K to 800 K predictions of Eq. (10) are more consistent with MD results than are the predictions of Eq. (11). This leads us to conclude that the viscosity temperature dependence in liquid HMX is more correlated... 

SELF-DIFFUSION COEFFICIENT AND ITS CORRELATION WITH VISCOSITY... 

The temperature dependencies of the viscosity (Figure 5.6) and the summation of the self-diffusion coefficient (Dcation + Oanion) (Figure 5.4) interestingly show the contrasted profiles with the indication of inverse relationship between viscosity and self-diffiision coefficient. This can be explained in terms of the Stokes-Einstein equation, which correlates the self-diffusion coefficient (Dcation Danion) with viscosity (q) by the following relationship ... 

Physical Mechanisms. The simplest interpretation of these results is that the transport coefficients, other than the thermal conductivity, of the water are decreased by the hydration interaction. The changes in these transport properties are correlated the microemulsion with compositional phase volume 0.4 (i.e. 60% water) exhibits a mean dielectric relaxation frequency one-half that of the pure liquid water, and ionic conductivity and water selfdiffusion coefficient one half that of the bulk liquid. In bulk solutions, the dielectric relaxation frequency, ionic conductivity, and self-diffusion coefficient are all inversely proportional to the viscosity there is no such relation for the thermal conductivity. The transport properties of the microemulsions thus vary as expected from simple changes in "viscosity" of the aqueous phase. (This is quite different from the bulk viscosity of the microemulsion.)... 

From the experimental data we were able to determine both the intramolecular and intermolecular relaxation rates as a function of pressure and temperature. The availability of shear viscosities and self-diffusion coefficients of EHB, which were measured earlier in our laboratory, provided the opportunity to test the dependence of the experimental cross-relaxation rates on viscosity and/or diffusion of EHB. The reorientational correlation time Tc describing overall molecular motion is coupled to the rj/T term through the Debye equation, which in a modified form is ... 

To make the significance of the NMR technique as an experimental tool in surfactant science more apparent, it is important to compare the strengths and the weaknesses of the NMR relaxation technique in relation to other experimental techniques. In comparison with other experimental techniques to study, for example, microemulsion droplet size, the NMR relaxation technique has two major advantages, both of which are associated with the fact that it is reorientational motions that are measured. One is that the relaxation rate, i.e., R2, is sensitive to small variations in micellar size. For example, in the case of a sphere, the rotational correlation time is proportional to the cube of the radius. This can be compared with the translational self-diffusion coefficient, which varies linearly with the radius. The second, and perhaps the most important, advantage is the fact that the rotational diffusion of particles in solution is essentially independent of interparticle interactions (electrostatic and hydrodynamic). This is in contrast to most other techniques available to study surfactant systems or colloidal systems in general, such as viscosity, collective and self-diffusion, and scattered light intensity. A weakness of the NMR relaxation approach to aggregate size determinations, compared with form factor determinations, would be the difficulties in absolute calibration, since the transformation from information on dynamics to information on structure must be performed by means of a motional model. 

Self-Diffusion. The self-diffusion coefficient D of liquid PH3 and PD3 in sealed tubes was determined by spin echo measurements of the nuclei H, h, and ip from 139 K to ambient temperature. Numerical values for both phosphanes are given by D(cm2/s) = 5.18x10" exp(-413/T) at temperatures up to 200 K. Above this temperature, D rises faster with temperature to reach 1.5x10 cm /s at 293 K. Attempts to correlate D and the viscosity t failed except at the lowest temperatures [11]. The self-diffusion constant of plastic crystalline PH3 was estimated for a vacancy diffusion mechanism on the basis of the spin-lattice relaxation time. The increase from D = 2x10" to 1x10" cm /s between 103 and 138 K is typical for a plastic crystal. A diffusion activation energy of 19 kJ/mol was estimated [12]. 

The foundations of DPD have been considered in a number of publica-tions. The rules of dissipative particle dynamics were derived from the underlying molecular interactions by a systematic coarse graining procedure. Evans derived expressions for the self-diffusion coefficient and shear viscosity of the DPD particles in the form of the Green-Kubo time correlation functions. DPD can be used to model arbitrarily shaped objects made up of fused spheres by... 

When the property calculated is a single particle property, such as the velocity autocorrelation function, or the particle s mean squared displacement, averaging over the particles does help a lot. Averaging over even a moderate number of particles of about 1000 decreases the error by more than an order of magnitude. Unfortunately, this is not possible for all properties. For instance, the calculation of viscosity calls for the stress correlation function [Eq. (67)], which is not a single particle property. This is why self-diffusion coefficients are usually estimated with much better accuracy than viscosity. 

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