Stochastic theory of the classical molecular dynamics method

Norman, G. É.; Stegaĭlov, V. V.

doi:10.1134/s2070048213040108

Cited by 138 publications

(33 citation statements)

References 87 publications

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“…The integration step is equal to 1.09 fs. Due to the local instability and mixing of phase trajectories of the system in the molecular dynamics calculation [1,3,20,21], the results should be averaged over an ensemble of independently obtained phase trajectories. In the calculations presented in this paper, averaging was carried out over five thousand independent phase trajectories.…”

Section: Methods For Determining the Effective Viscosity Coefficientmentioning

confidence: 99%

Molecular dynamics simulation of fluid viscosity in nanochannels

Rudyak¹,

Belkin²

2018

Nanosystems: Phys. Chem. Math.

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The viscosity of fluids in a plane nanochannel has been studied by molecular dynamics method. The effective viscosity coefficient was determined using the fluctuation-dissipation theorem derived previously by the authors from the nonequilibrium statistical theory of fluid transport in confined conditions. It has been found that the fluid viscosity in a nanochannel is strongly dependent on the interaction potential between the fluid and channel wall molecules. In particular, increasing the depth of the potential well of this interaction leads to an increase in the viscosity. At the same time, if the depth of the potential well is small, the fluid viscosity in a nanochannel may be even lower than its viscosity in an unconfined (bulk) system. Thus, the fluid viscosity in a nanochannel and hence the channel flow resistance can be varied by changing the material of the nanochannel walls.

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Section: Methods For Determining the Effective Viscosity Coefficientmentioning

confidence: 99%

Molecular dynamics simulation of fluid viscosity in nanochannels

Rudyak¹,

Belkin²

2018

Nanosystems: Phys. Chem. Math.

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“…Using molecular modeling approach [27] dependence of horizontal and vertical energy on time was obtained for a various sets of parameters. Graphics presented in this paper are corresponding to the next one: λ = 0.01 s −1 , δq = 0.1, Ω = 4 × 10 4 s −1 , Z = 10 4 , e ′ = −40 cm −1 , ε = 0.08, k = 30 cm −1 , q ′ z = 0.03 cm −1 .…”

Section: Results Of Modelingmentioning

confidence: 99%

Energy transfer between degrees of freedom of a dusty plasma system

Semyonov

Тимофеев

2016

J. Phys.: Conf. Ser.

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Abstract. Dust particles under certain conditions can acquire kinetic energy of the order of 10 eV and higher, far above the temperature of gas and temperatures of ions and electrons in the discharge. Such heating can be explained by the energy transfer between degrees of freedom of a dusty plasma system. One of the mechanisms of such energy transfer is based on parametric resonance. A model of dust particles system in gas discharge plasma including fluctuations of dust particles charge and features of near-electrode layer is presented. Molecular dynamics simulation of the dust particles system is performed. Conditions of the resonance occurrence are obtained for a wide range of parameters.

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“…Diffusivity is in a fair agreement with [9], where only Green-Kubo approach is applied. The discrepancy for the shear viscosity can be attributed to the uncertainty of the evaluation of the tail contribution in (2) and possible difference in the cut-off time at the integration.…”

Section: Lennard-jones Systemmentioning

confidence: 99%

“…The starting point for every segment is chosen in every certain number of steps. Each segment is chosen to be statistically independent [2] and the coefficient is found for each of them. The ensemble averaging is substituted for the time averaging over reference times in the equations (2), (4) - (6).…”

Section: Simulationmentioning

confidence: 99%

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Viscosity calculations at molecular dynamics simulations

Kirova

Norman

2015

J. Phys.: Conf. Ser.

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Abstract. Viscosity and diffusion are chosen as an example to demonstrate the universality of diagnostics methods in the molecular dynamics method. To emphasize the universality, three diverse systems are investigated, which differ from each other drastically: liquids with embedded atom method and pairwise interatomic interaction potentials and dusty plasma with a unique multiparametric interparticle interaction potential. Both the Einstein-Helfand and Green-Kubo relations are used. Such a particular process as glass transition is analysed at the simulation of the aluminium melt. The effect of the dust particle charge fluctuation is considered. The results are compared with the experimental data.

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Stochastic theory of the classical molecular dynamics method

Cited by 138 publications

References 87 publications

Molecular dynamics simulation of fluid viscosity in nanochannels

Molecular dynamics simulation of fluid viscosity in nanochannels

Energy transfer between degrees of freedom of a dusty plasma system

Viscosity calculations at molecular dynamics simulations

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