Radial Distribution Function

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A Radial Distribution Function is a continuous probability function based on the distance from a reference particle.



References

2015

  • (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/radial_distribution_function Retrieved:2015-2-14.
    • In statistical mechanics, the radial distribution function, (or pair correlation function) [math]\displaystyle{ g(r) }[/math] in a system of particles (atoms, molecules, colloids, etc.), describes how density varies as a function of distance from a reference particle.

      If a given particle is taken to be at the origin O, and if [math]\displaystyle{ \rho =N/V }[/math] is the average number density of particles, then the local time-averaged density at a distance [math]\displaystyle{ r }[/math] from O is [math]\displaystyle{ \rho g(r) }[/math]. This simplified definition holds for a homogeneous and isotropic system. A more general case will be considered below.

      In simplest terms it is a measure of the probability of finding a particle at a distance of [math]\displaystyle{ r }[/math] away from a given reference particle, relative to that for an ideal gas. The general algorithm involves determining how many particles are within a distance of r and r+dr away from a particle. This general theme is depicted to the right, where the red particle is our reference particle, and blue particles are those which are within the circular shell, dotted in orange.

      The RDF is usually determined by calculating the distance between all particle pairs and binning them into a histogram. The histogram is then normalized with respect to an ideal gas, where particle histograms are completely uncorrelated. For three dimensions, this normalization is the number density of the system multiplied by the volume of the spherical shell, which mathematically can be expressed as [math]\displaystyle{ g(r)_I = 4\pi r^2\rho dr }[/math], where [math]\displaystyle{ \rho }[/math] is the number density.

      Given a potential energy function, the radial distribution function can be computed either via computer simulation methods like the Monte Carlo method, or via the Ornstein-Zernike equation, using approximative closure relations like the Percus-Yevick approximation or the Hypernetted Chain Theory. It can also be determined experimentally, by radiation scattering techniques or by direct visualization for large enough (micrometer-sized) particles via traditional or confocal microscopy.

      The radial distribution function is of fundamental importance in thermodynamics because the macroscopic thermodynamic quantities can usually be determined from [math]\displaystyle{ g(r) }[/math].