Paper Number
SF12 

Session
Self-assembly and Flow-induced Systems/Gels

Title
Mesoscopic modeling and simulation of transiently networked fluids/gels

Presentation Date and Time
October 6, 2014 (Monday) 4:25

Track / Room
Track 6 / Washington C

Authors (Click on name to view author profile)

1. Zhou, Lin (New York City College of Technology, CUNY, Mathematics Department)
2. Cook, L.Pamela (University of Delaware, Department of Mathematical Sciences)

Author and Affiliation Lines (in printed abstract book)
Lin Zhou¹ and L.Pamela Cook^2
1Mathematics Department, New York City College of Technology, CUNY, Brooklyn, NY 11201; ²Department of Mathematical Sciences, University of Delaware, Newark, DE 19716

Speaker / Presenter 
Zhou, Lin

Text of Abstract
Wormlike micellar solutions have been studied primarily through macroscopic models and their numerical simulation. Most such models predict an exponential decay in time in the (small amplitude) stress relaxation response. However, experiments show that as the concentration of the micelles increases, micellar solutions exhibit a stretched exponential or a power-law stress relaxation. These slow relaxation processes are similar to that of many biopolymer networks and physically cross-linked gels.

To understand the behavior of wormlike micellar solutions in both (exponential relaxation and slower/power-law relaxation) regimes, we consider the mesoscopic simulation of transient networks in which the connecting chains can break free and can reconnect to the network at randomly distributed sticky nodes (van den Brule and Hoogerbrugge, JNNFM 1995). The motion of the beads and junctions (nodes with beads) are governed by a Langevin equation. We explore the effect of the attachment/detachment rate of the sticky nodes and the effect that the number of beads that are allowed to connect to the sticky node has on the shear stress response of the networked system. The inclusion of the topology of the network in the simulations allows the entire system to reorganize in response to localized breakages. Stochastic simulations based on different probability distribution functions will be analyzed to understand the slow relaxation processes.