A python implementation of the Fundamental Measure Theory for hard-sphere mixture in classical Density Functional Theory
For a fluid composed by hard-spheres with temperature T, total volume V, and chemical potential of each species
where
The ideal-gas contribution
where
The hard-sphere contribution,
where $ n_\alpha(\boldsymbol{r}) = \sum_i \int_{V} d \boldsymbol{s}\ \rho_i (\boldsymbol{s})\omega^{(\alpha)}_i(\boldsymbol{r}-\boldsymbol{s})$ are the weigthed densities given by the convolution with the weigth function
- Rosenfeld Functional (RF) - Rosenfeld, Y., Phys. Rev. Lett. 63, 980–983 (1989)
- White Bear version I (WBI) - Yu, Y.-X. & Wu, J., J. Chem. Phys. 117, 10156–10164 (2002); Roth, R., Evans, R., Lang, A. & Kahl, G., J. Phys. Condens. Matter 14, 12063–12078 (2002)
- White Bear version II (WBII) - Hansen-Goos, H. & Roth, R. J., Phys. Condens. Matter 18, 8413–8425 (2006)
where [x] represents the implemented functionals.
The thermodynamic equilibrium is given by the functional derivative of the grand potential in the form
On the folder 'examples' you can find different applications of the FMT.
Fig.5 - The radial distribution function of a pure hard-sphere fluid with bulk density ρ_b = 0.2. | Fig.6 - The radial distribution function of a pure hard-sphere fluid with bulk density ρ_b = 0.9. |