On-demand emulsions from oscillatory two-phase shear flows

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Solvent extraction across a liquid-liquid interface is a diffusion-limited process that relies on the dispersion of one phase in the other to maximise the surface area between the phases, e.g., the purification of nuclear fuel in the PUREX process. Similarly, chemical reaction kinetics in liquid liquid systems, e.g., nitration of aromatics, are controlled by the rate of generation interfacial area. Surfactant-stabilized emulsification of the two phases is routinely used to disperse them. However, this creates industrial design challenges because of the added requirement of rapid phase separation following the process. The project aims to propose a purely hydrodynamic method to generate on-demand stabilizer-free emulsions through external forcing, which rapidly return to separated phases upon interruption of the forcing.The specific objectives are threefold: a) characterize the fundamental interface breakup mechanism which relies on competition between inertial, viscous, and surface tension forces; b) tailor emulsion properties depending on the fluid properties and vibrational parameters; c) use the fluid mechanical device to optimize on-demand solvent extraction. We will use a combined approach of quantitative experiments and Lattice-Boltzmann (LB) simulations to gain insights into interface breakup with a focus on deriving simple models for interface breakup in two-layer oscillatory shear flows (objective (a) & (b)). Herein we will additionally characterize interface breakup in two-phase systems where one fluid exhibits non-Newtonian properties. We then turn to the development of a laboratory model of solvent extraction and provide a proof-of-concept of our system and evaluate its efficiency depending on the vibrational regime (objective (c)). The proposed project will not only advance fundamental understanding of interface breakup in both Newtonian and complex fluids but also potentially offer new design solutions for industrial diffusion-limited processes.