Flow, Memory and Aging of Soft Particle Pastes

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This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).0854420BonnecazeIntellectual Merit: Many concentrated materials consist of soft particles (e.g., emulsions, elastic particles, microgels, star polymers or polymer-coated particles) packed and deformed into an amorphous state. These pastes are important as rheological modifiers for food, materials and coating processes, friction reduction in cement pumping and hydrofracturing. There are, however, several aspects of their behavior that are not fully understood. Soft particle pastes (SPPs) display complex shear thinning, normal and yield stresses, coating instabilities, slip, memory and aging. Their aging behavior is similar to that in structural, spin and polymer glasses. We propose to develop simulations and models to describe the behavior of these soft-particle pastes in order to: 1) develop a complete rheological model for soft particle pastes with arbitrary interparticle potentials to describe their elasto-plastic flow; 2) identify the microstructural events that occur during flow and that give rise to aging and memory in soft particle pastes in order to accelerate, stop or otherwise mitigate these effects; 3) test existing theories of aging and develop a new theory for aging and memory of these materials specifically accounting for the elastohydrodynamic interactions. To achieve these goals we will build on our discovery of the importance of elastohydrodynamic interactions for these materials and our recent simulations and experiments on the viscoelastic properties of microgel suspensions undergoing shear. Specifically, we will: 1) develop a theory to describe the microstructure in terms of the pairwise, particle distribution function of the relaxed, unstrained paste for arbitrary interparticle forces and predict elastic properties of SPPs; 2) develop a theory that determines the perturbed distribution function under flow and thus predict the yield strength and the general viscoelastic properties of SPPs; 3) modify our existing 3D particle-based dynamic simulation of soft particle pastes to simulate aging and memory; 4) use the simulations for parametric studies of aging and memory of soft particle pastes correlating macroscopic behavior and microstructural rearrangements; 5) evaluate existing models and develop new models for the bulk rheology, aging and memory of soft particle pastes. For all stages of this work, we will continually compare our theoretical predictions to experiments in the literature and those conducted by a collaborator at the ESPCI. The simulations will allow the direct connection between the macroscopic properties (e.g., yield stress, modulus, effective viscosity, normal stresses, aging and memory) to the microscopic interactions of the soft particles and a fundamental understanding of the origins of their rheology. Broader Impacts: The rheology of SPPs appears to be universal across a broad array of deformable particles ranging in size from nanometers to hundreds of microns. The knowledge gained from this work will provide engineers and colloid scientists a means to tailor the formulation of soft particle pastes to have desired rheological properties. Theories from this proposed work for predicting the non-equilibrium microstructure will also provide a new methodology for modeling the properties of highly concentrated, amorphous suspensions of soft particles and other complex fluids. The aging and memory phenomena seen in pastes are also seen in many other systems, including nematic polymers and spin and structural glasses. The proposed work will provide fundamental insights into these behaviors. The aging phenomenon in pastes is part of a broader issue of and an industrially important concern about shelf life of formulations of suspensions. The results of this work will provide guidance into controlling aging and shelf-life. This proposed will involve the education of one graduate student and two undergraduate students over the course of the project. They will become skilled in rheology of complex fluids, computational simulation and modeling.