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Diffusion Model of Lennard-Jones Fluids Based on the Radial Distribution Function.

Xiangfei Ji1

  • 1School of Chemistry and Chemical Engineering, Shanxi University, 030006Taiyuan, China.

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A new theoretical model explains diffusion in Lennard-Jones fluids by analyzing molecular transport in radial distribution function space. This model accurately predicts self-diffusion coefficients across various densities and temperatures, aiding fluid dynamics research.

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Area of Science:

  • Physical Chemistry
  • Computational Fluid Dynamics
  • Statistical Mechanics

Background:

  • Diffusion is crucial for understanding fluid behavior.
  • Existing models for Lennard-Jones fluids have limitations over wide density ranges.
  • Accurate diffusion modeling requires understanding molecular interactions and transport properties.

Purpose of the Study:

  • To develop a theoretical model for diffusion in Lennard-Jones fluids.
  • To extend diffusion modeling to a broader density range.
  • To accurately predict self-diffusion coefficients using a novel approach.

Main Methods:

  • Theoretical modeling of molecular transport in radial distribution function space.
  • Calculation of mean free path from radial distribution functions.
  • Adaptation of the rarefied hard sphere gas diffusion model.
  • Incorporation of corrections for collision frequency and backscattering effects.
  • Molecular dynamics simulations for validation.

Main Results:

  • A theoretical model for diffusion in Lennard-Jones fluids was successfully developed.
  • The model relates static properties (radial distribution function) to dynamic properties (mean free path).
  • Predicted self-diffusion coefficients show good agreement with molecular dynamics simulations.
  • The model performs well across a wide range of reduced densities (0.298–1.19) and temperatures (0.833–1.67), with minor deviations at very high densities.

Conclusions:

  • The proposed theoretical model provides an effective framework for diffusion in Lennard-Jones fluids.
  • Treating molecular transport in radial distribution function space is a viable approach.
  • The model offers improved accuracy for self-diffusion coefficient predictions in dense fluids.
  • This work advances the understanding of transport phenomena in dense fluids.