A rheological state diagram for rough colloids in shear flow
  The flow of dense suspensions, glasses, and granular materials is heavily influenced by frictional interactions between constituent particles. However, neither hydrodynamics nor friction has successfully explained the full range of flow phenomena in concentrated suspensions. Particles with asperities represent a case in point. Lubrication hydrodynamics fail to completely capture two key rheological properties - namely, that the viscosity increases drastically and the first normal stress difference can switch signs as volume fraction increases. Yet, simulations that account for interparticle friction are also unable to fully predict these properties. Furthermore, experiments show that rheological behavior can vary depending on particle roughness and deformability. We seek to resolve these apparent contradictions by systematically tuning the roughness of model colloids, investigating their viscosity and first normal stress differences under steady shear, and finally generating a rheological state diagram that demonstrates how surface roughness influences the transition between shear thickening and dilatancy. Our simulations, which are in good agreement with the experiments, suggest that friction between rough particles is significant. In addition, we find that roughness progressively lowers the critical conditions required for the onset of shear thickening and dilatancy. Our results thus provides a major contribution in the field of suspension rheology with broad relevance to granular and particulate materials. For instance, particle geometry can be tuned to increase the efficacy of materials that turn solid-like on the application of stimuli. On the other hand, engineers who work with concentrated slurries can now use images of the constituent particles to estimate optimal flow processing conditions. 
Lilian C. Hsiao, Safa Jamali, Daniel J. Beltran-Villegas, Emmanouil   Glynos, Peter F. Green, Ronald G. Larson and Michael J...
cond-mat.soft cond-mat.mtrl-sci