You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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 $\mu_i$ specified, the grand potential, $\Omega$, is written as
where $k_B$, and $\Lambda_i$ is the well-known thermal de Broglie wavelength of each component.
The hard-sphere contribution, $F^{\textrm{hs}}$, represents the hard-sphere exclusion volume correlation described by the fundamental measure theory (FMT) as
$$F^\text{hs}[{\rho_i (\boldsymbol{r})}] = k_B T\int_{V} d \boldsymbol{r}\ \Phi_\textrm{FMT}({ n_\alpha(\boldsymbol{r})})$$
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 $\omega^{(\alpha)}_i(\boldsymbol{r})$. The function $\Phi$ can be described using different formulations of the fundamental measure theory (FMT) as