Non-gaussian velocity correlations in fluids

Balucani, U.; Tognetti, V.; Vallauri, R.; Grigolini, Paolo; Marin, Paolo

doi:10.1007/bf01313025

Cited by 17 publications

(3 citation statements)

References 16 publications

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“…It should be noticed that similar non-Gaussian features, which are associated with the nonlinearities of the microscopic interactions, were already observed from the analysis of the atomic velocities. ~15' 28~ Although the GLE for a system of interacting non-Brownian particles has not been theoretically demonstrated, the statistical properties of the R(t) forces generated from MD simulations using the GLE are the ones ordinarily required for the random forces (13)- (15). Moreover, computer simulations based on the GLE and assuming a Gaussian distribution of R(t) permit quite good reproductions of the analyzed structural and dynamical properties of the solute [g(r), C(t), D, O(t), G(r, t),...].…”

Section: Discussionmentioning

confidence: 99%

On the description of atomic motions in dense fluids by the generalized Langevin equation: statistical properties of random forces

1990

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The suitability of the generalized Langevin equation (GLE) for a realistic description of the behavior of a system of interacting particles in solution is discussed. This study is focused on the GLE for a system of non-Brownian particles, i.e., the masses and the sizes of the solute particles are similar to those of the bath particles. The random and frictional forces on the atoms of the solute due to their collisions with the solvent atoms are characterized from molecular dynamics simulations of simple dense liquid mixtures. The required effective memory functions, which are dependent on the concentration of solute, are obtained by solving a generalized Volterra equation. The validity of the usual assumptions on the statistical properties of the random forces is carefully analyzed, paying special attention to their Gaussianity. The reliability of stochastic simulations based on the GLE is also discussed.

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Section: Discussionmentioning

confidence: 99%

On the description of atomic motions in dense fluids by the generalized Langevin equation: statistical properties of random forces

1990

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“…It has been reported in the literature that non-Gaussian behavior is also observed in the velocity autocorrelation function of dense bulk fluids. 22,23 To show the generality of these observations to a different confining surface, we use the formulation to study thermal noise for SPC/E water confined inside a 4σ oo wide semi-infinite silicon slit pore. This system is also loaded at a reference bulk state of 33.3 molecules/nm 3 and 300 K temperature.…”

Section: Thermal Noise In Molecular Fluidsmentioning

confidence: 99%

Thermal noise in confined fluids

Sanghi

Aluru

2014

The Journal of Chemical Physics

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In this work, we discuss a combined memory function equation (MFE) and generalized Langevin equation (GLE) approach (referred to as MFE/GLE formulation) to characterize thermal noise in confined fluids. Our study reveals that for fluids confined inside nanoscale geometries, the correlation time and the time decay of the autocorrelation function of the thermal noise are not significantly different across the confinement. We show that it is the strong cross-correlation of the mean force with the molecular velocity that gives rise to the spatial anisotropy in the velocity-autocorrelation function of the confined fluids. Further, we use the MFE/GLE formulation to extract the thermal force a fluid molecule experiences in a MD simulation. Noise extraction from MD simulation suggests that the frequency distribution of the thermal force is non-Gaussian. Also, the frequency distribution of the thermal force near the confining surface is found to be different in the direction parallel and perpendicular to the confinement. We also use the formulation to compute the noise correlation time of water confined inside a (6,6) carbon-nanotube (CNT). It is observed that inside the (6,6) CNT, in which water arranges itself in a highly concerted single-file arrangement, the correlation time of thermal noise is about an order of magnitude higher than that of bulk water.

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“…From the wide body of results provided by computer simulation, it appears that variables of interest such as linear [17] and angular [18] velocities cannot be described in terms of Gaussian non-Markovian statistics. On the other hand, as repeatedly stressed by van Kampen [ 191, the only family of stochastic processes unquestionably admitting equations of the standard Fokker-Planck form to be used is the class of the Gaussian non-Markovian stochastic processes.…”

Section: On the Preparation Of A Non-linear "Microscopic" Model Ofmentioning

confidence: 99%

Non-Linear and Non-Markovian Effects in Relaxation Processes: Application to Molecular Dynamics

Marchesoni¹

1984

Phys. Scr.

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Some preparation effects in the relaxation processes of complex statistical systems are discussed. By studying a simpler one-dimensional case, a clearcut distinction between the role of non-linearity and that of non-Markovian statistics emerges. The influence of preparation through nonlinearity is shown to be extremely persistent. A detailed analysis of a more complicated model describing de-excitation processes in rotational molecular dynamics in the liquid state, where both of these ingredients are accounted for, supports our theoretical prediction. Our conclusions apply to the results of most computer simulations of complex physical systems.

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Non-gaussian velocity correlations in fluids

Cited by 17 publications

References 16 publications

On the description of atomic motions in dense fluids by the generalized Langevin equation: statistical properties of random forces

On the description of atomic motions in dense fluids by the generalized Langevin equation: statistical properties of random forces

Thermal noise in confined fluids

Non-Linear and Non-Markovian Effects in Relaxation Processes: Application to Molecular Dynamics

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