Ornstein–Zernike equation

E835194

The Ornstein–Zernike equation is a fundamental relation in statistical mechanics that links the total and direct correlation functions of a fluid, forming the basis for many liquid-state theories and approximations.

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Predicate Object
instanceOf equation in statistical mechanics
integral equation
theoretical physics concept
appliesTo classical fluids
colloidal suspensions
liquid mixtures
polymer solutions
simple liquids
assumes homogeneous fluid
isotropic fluid
basisFor Percus–Yevick approximation NERFINISHED
hypernetted-chain approximation
liquid-state integral equation theories
mean spherical approximation
mode-coupling theories of liquids
reference interaction site model NERFINISHED
describes relation between total and direct correlation functions in a fluid
field condensed matter physics
liquid-state theory
statistical mechanics
generalizedTo anisotropic fluids
molecular fluids with orientational degrees of freedom
multicomponent mixtures
hasForm h(r12) = c(r12) + ρ ∫ d r3 c(r13) h(r32)
hasFourierSpaceForm h(k) = c(k) + ρ c(k) h(k)
historicalContext introduced to explain long-range density correlations near the critical point of fluids
implies S(k) = 1 + ρ h(k)
S(k) = 1 / [1 − ρ c(k)]
involves convolution of correlation functions
number density ρ
namedAfter Frits Zernike NERFINISHED
Leonard Ornstein NERFINISHED
relatedTo critical opalescence
fluctuation–dissipation theorem NERFINISHED
pair distribution function g(r)
relates direct correlation function c(r)
total correlation function h(r)
usedFor analysis of scattering experiments
calculation of pair correlation functions
calculation of structure factor S(k)
computation of thermodynamic properties of liquids
description of critical phenomena in fluids
description of density fluctuations
usedIn X-ray scattering analysis of liquids
light scattering analysis of fluids
neutron scattering analysis of liquids
yearProposed 1914

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Kirkwood approximation in statistical mechanics relatedTo Ornstein–Zernike equation
subject surface form: Kirkwood approximation