  Employing the discrete element method, we study the rheology of dense
granular media mixtures, varying in size, density, and frictional properties of
particles, across a spectrum from quasi-static to inertial regimes. By
accounting for the volumetric contribution of each solid phase, we find that
the stress ratio, $\mu$, and concentration $\phi$, scale with the inertial
number when using volume averaging to calculate mean particle density, friction
and size. Moreover, the critical packing fraction correlates with skewness,
polydispersity, and particle friction, irrespective of the size distribution.
Notably, following the work of Kim and Kamrin [2020] we introduce a rheological
power-law scaling to collapse all or monodisperse and polydisperse data,
reliant on concentration, dimensionless granular temperature, and the inertial
number. This model seamlessly merges the $\mu(I)$-rheology and Kinetic Theory,
enabling the unification of all local and non-local rheology data onto a single
master curve.
