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Quantifying the influence of rolling friction on force networks and rheology in sheared suspensions

ORAL

Abstract

The mechanism of shear thickening in dense suspensions has been linked to a stress-controlled transition from an unconstrained lubricated ``frictionless'' to a constrained unlubricated ``frictional'' rheology. Particle simulations that led to this concept have been successful in quantitatively reproducing the non-Newtonian behavior of thickening suspensions. We have recently shown the importance of rolling friction for the quantitative agreement of numerical simulations with the experimental data. Rolling friction can stabilize the force network, and hence lead to higher effective viscosity under shear. With an aim to make a connection between the frictional force network and the rheology, we perform persistent homology on systems with different combinations of sliding and rolling friction at several volume fractions. These measures allow for quantifying the force network properties that are responsible for the modified rheology of sheared suspensions. We will present the comparison between the statistics of the evolution of the force network in different systems and how different constraints affect the rheology of a dense suspension.

Presenters

  • Abhinendra Singh

    University of Chicago

Authors

  • Abhinendra Singh

    University of Chicago

  • Rituparna Basak

    New Jersey Institute of Technology, Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, New Jersey Institute of Technology, Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, New Jersey Institute of Technology, USA

  • Juan De Pablo

    University of Chicago, Molecular Engineering, University of Chicago, Institute for Molecular Engineering, University of Chicago, The Pritzker School of Molecular Engineering, University of Chicago

  • Lou Kondic

    New Jersey Institute of Technology, Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, New Jersey Institute of Technology, Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, New Jersey Institute of Technology, USA

  • Heinrich Jaeger

    Department of Physics, University of Chicago, University of Chicago