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Droplet-based microfluidic device for multiple-droplet clustering
Authors:Xu Jing  Ahn Byungwook  Lee Hun  Xu Linfeng  Lee Kangsun  Panchapakesan Rajagopal  Oh Kwang W
Institution:Sensors and MicroActuators Learning Lab, Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA.
Abstract:We present a multiple-droplet clustering device that can perform sequential droplet trapping and storing. Shape-dependent droplet manipulation in forward and backward flows has been incorporated to achieve high trapping and storing efficiency in a 10 × 12 array of clustering structures (e.g., storing well, storing chamber, trapping well, and guiding track). In the forward flow, flattened droplets are trapped in each trapping well. In the backward flow, the trapped droplets are released from the trapping well and follow the guiding tracks to their corresponding storing wells. The guided droplets float up out of the confining channel to the super stratum of the storing chamber due to interfacial energy and buoyancy effects. This forward/backward flow-based trapping/storing process can be repeated several times to cluster droplets with different contents and samples in the storing chambers. We expect that the proposed platform will be a valuable tool to study complex droplet-based reactions in clustered droplets.
Keywords:
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