Chain Failure Events in Microfluidic Membrane Networks

Multiple lipid encased water droplets may be linked together in oil to form large networks of droplet interface bilayers thus creating a new class of stimuli-responsive materials for applications in sensing, actuation, drug delivery, and tissue engineering. While single droplet interface bilayers have been extensively studied, comparatively little is known about their interaction in large networks. One particular problem of interest is understanding the impact of the coalescence of two neighboring droplets on the overall structural integrity of the network. Here, we propose a computational modeling scheme that predicts and characterizes the mechanical properties of the multiple lipid bilayer interfaces within the droplet network upon intentional coalescence of adjacent droplets. Droplet networks with tailored architectures are synthesized with the aid of magnetic motor droplets containing a biocompatible ferrofluid. The equilibrium configuration of the droplet networks is compared to computational prediction which defines the overall stability by summing the interfacial energies. Once the networks are completed, failure in selected membranes is induced. As the targeted droplets coalesce together, the equilibrium structure of the network is altered and the remaining droplets may shift to new configurations dictated by their minimized mechanical energies.