Magnetic Field-Driven Deformation, Attraction, and Coalescence of Nonmagnetic Aqueous Droplets in an Oil-Based Ferrofluid.

Abstract

Stimuli-responsive compartments are attracting more and more attention through the years motivated by their wide applications in different fields including encapsulation, manipulation, and triggering of chemical reactions on demand. Among others, magnetic responsive compartments are particularly attractive due to the numerous advantages of magnetic fields compared to other external stimuli. In this article, we used an oil-based ferrofluid where the magnetic nanoparticles have been coated with different polymers to increase their amphiphilic character and surface activity, consequently rendering the interface magnetically responsive. Microliter aqueous nonmagnetic droplets dispersed in the oil-based ferrofluid were used as a model of microreactors. A comprehensive experimental and theoretical study of the deformation, attraction, and coalescence processes of the nonmagnetic water droplets coated with the magnetic nanoparticles under an applied magnetic field in the continuous oil-based ferrofluid phase is provided. To manipulate the packing of the nanoparticles at the water/oil interface, the ionic strength of the aqueous droplets was varied using different NaCl concentrations, and its effect on modulating the coalescence of the droplets was probed. Our results show that the water droplets deform along the magnetic field depending on the magnetic properties of the ferrofluid itself and on the surface properties of the interface, attract in pairs under the action of the magnetic dipole force, and coalesce by the action of the same force with a stochastic behavior. We have studied all of these phenomena as a function of the magnetic field applied, evaluating in each case the forces and/or pressures acting on the droplets with particular attention to roles of magnetic attraction, interface properties, and viscosity in the system. This work offers an overall set of tools to understand and predict the behavior of multiple water droplets in an oil-based ferrofluid for lab-on-a-chip applications.