CBE Seminar: Network Science for Understanding the Physics and Rheology of Colloidal Suspensions

Non-UCI people, please use this registration link: https://forms.gle/msDt5B4mvgQ1wFrf6

Abstract: Colloidal particles suspended in a simple fluid, depending on their packing fraction and interactions can exhibit a wide range of exotic rheological behavior. For instance, when in large fractions, they may resist to large deformations under flow, which is best exemplified by running on a pool of cornstarch and water. When attractive interactions are induced between colloids, they can assemble into space spanning networks with mechanical properties of a viscoelastic solid, aka colloidal gels. Over the past couple of decades, and owing to a tremendous advance in our experimental and computational capabilities, we have built an understanding of the complex dynamics that give rise to such physical and rheological behavior: rather than particle-scale micromechanics, it is the collective dynamics of the colloids at a coarser scale that control the macroscopic/bulk properties of a particulate system. Whether it’s a force network that carries the highest stresses in a shear thickening suspension, or a porous network of particles that gives a gel its elasticity, it is a “network” referring to the collective particle dynamic/behavior that is responsible for the physical characteristics of a system. Thus, understanding the physics of this particulate network is the key to controlling and designing particulate systems with desirable properties. I will discuss how borrowing well-established concepts from network science can help us interrogate and characterize these particulate networks and build a coarse-grained description of the system. These mesoscale structures, identified through community detection techniques that are commonly used in social or economic networks, provide a new understanding of physics and rheology in dense suspensions as well as attractive colloidal gels. Finally, I will discuss some of the unexplored avenues and potential directions in which these new techniques can make an impact.

Bio: Safa Jamali is an assistant professor of mechanical and industrial engineering at Northeastern University. He received his doctorate from Case Western Reserve University’s Department of Macromolecular Science, followed by two years of postdoc training at MIT’s Departments of Chemical Engineering, Mechanical Engineering and the Energy Initiative, and then he joined Northeastern University in 2017. His research group is focused on developing and using a series of data-driven and computational methods for physics and rheology of complex materials. These include biophysics of cell suspensions with focus on blood dynamics, science-based data-driven methods and machine-learning platforms for rheological applications, and physics of colloidal systems amongst other topics.

Host: Professor Ali Mohraz