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The hydrodynamic separation of spherical particles in flows at low Reynolds numbers is a very active area of research in microfluidic engineering due to the many important biomedical applications. In particular, curved channels such as spiral channels are of growing interest because the lift and drag force exerted on inertial particles can be used to hydrodynamically separate the particles. In this paper we present a scale invariant classification of the lateral focusing of particles in highly curved spiral micro channels with a square cross section. We then use this scale invariant classification to demonstrate the separation of particles in two-particle mixtures across a large range of sizes. We thus show that our results can be used to systematically design the geometry of devices and select flow parameters to separate particles by size in a mixture.

Bioartificial pancreas made of insulin-secreting islets cells holds great promise in the treatment of individuals with Type-1 diabetes. Successful islet cell microencapsulation in biopolymers is a key step for providing immunoisolation of transplanted islet cells. Because of the variability in the size and shape of pancreatic islets, one of the main obstacles in their microencapsulation is the inability to consistently control shape, size, and microstructure of the encapsulating biopolymer capsule. In this chapter, we provide a detailed description of a microfluidic approach to islet cell encapsulation in alginate that might address the microencapsulation challenges.

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Stiffness based sorting of mixed paper waste at high speed is desirable for sorting board, cardstock, and paper from each other for efficient recycling. We propose a quick, non-contact method for measuring the relative stiffness of paper samples moving on a conveyor at high speeds. The method consists of impinging an air jet on a moving paper sample while it is crossing a gap during transfer from one conveyor belt to another. The deflection caused by the impinging air jet can be measured and used to categorize different grades of paper. In this paper, we report results from a simulation of the proposed method using a finite element model. Influence of conveyor speed, sample orientation and nozzle pressure is studied using the model. Results indicate that the stiffness estimation has sufficient resolution to distinguish between board and paper grades at high conveyor speeds.