It is well-known that mixing granular materials consisting of particles with different properties (e.g. size, density, etc.) is generally a difficult task as the different particles will tend to segregate. An additional difficulty in granular mixing arises when particle cohesion is significant, as particles form agglomerates. Of course, homogeneous granular materials feature an even distribution of their components and physical and chemical properties that are constant throughout the materials, and so they are generally more desirable than inhomogeneous materials. In addition, when the range of grain size is sufficiently large so the smaller particles can fit in the gaps between packed larger particles, improving homogeneity can potentially result in increasing solids loading. As such, it is of great interest to explore how the homogeneity of cohesive granular materials featuring particles with a large size range can be controlled. The ultimate goal of my research is to develop models that can be used to predict the homogeneity of such materials given the properties of the particles and interstitial fluid and mixing conditions.
Through the use of discrete element method (DEM) simulations, I have modeled the shear mixing of bidisperse collections of spherical particles with a 7:1 diameter ratio. In these simulations, cohesion arose by having the particles attract each other via the van der Waals force, and I have examined the influence of particle cohesion on mixture homogeneity by performing simulations with various particle Hamaker constants. I have also investigated the influences of gravity, shear rate, and the viscosity of an interstitial fluid on mixture homogeneity. Through the use of several order statistics as well as microstructure images, I will show how the homogeneity of these mixtures can be controlled.