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Tuesday, February 6, 2018 at 12:00pm
High throughput accurate sorting of colloidal particles is a key component of advances in a range of fields, from cellular biology to physical chemistry. For this purpose, microfluidic devices have been designed that manipulate colloidal particle transport in microfluidic channels based on particle size, exploiting a transport phenomenon termed “deterministic lateral displacement” (DLD). However, such microdevice designs are only well-suited for simple particle manipulations, are not oriented towards handling continuously polydisperse suspensions, and exploit only one mode of microfluidic transport.
The focus of this talk is to present our efforts on novel design procedures for microfluidic devices of this type, which are well-suited to handle any kind of polydisperse suspension/desired output configuration by exploiting a potentially infinite number of transport modes. We first discuss how the particle dynamics of DLD in these devices leads to fractal lateral displacement functions of particle size, and follow by utilizing techniques from real analysis to show that chained devices can replicate any target output displacement function that is Lebesgue measurable. We conclude by demonstrating design solutions for some example target functions, obtained by solving highly nonlinear optimization problems, and compare our strategies/results to other approaches.
Cornell Engineering, Sibley School of Mechanical and Aerospace Engineering, Engineering
the public.
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