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Full Version: Nanoventions Micro-optic Modeling and Control of Micro-Scale Systems
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On the macro scale, feedback control is routinely applied to improve performance and enable new tasks in complex and uncertain systems operating in noisy environments. Our lab has focused on applying feedback control ideas to systems on the micro scale. Here we show how control methods can improve existing performance in the UCLA lab-on-a-chip electrowetting system and can create entirely new capabilities in our 'micro fluidic tweezers' cell steering devices.In the Electro-Wetting-On-Dielectric (EWOD) system developed at UCLA by CJ Kim, a grid of electrodes is used to locally change surface tension forces on liquid droplets. By choosing the electrode firing sequence it is possible to move, split, join, and mix liquids in the droplets. We present an experimentally validated 2-phase fluid flow model of the liquid dynamics, and then show the development of control algorithms validated on this model. Control ideas and real time image algorithms are presented for controlling material points on the liquid/gas boundaries, for precision splitting of droplets, for steering of particles inside the droplets, and for dealing with external noise source. Nanoventions has developed a number of low-cost, complex micro-optic polymer film and particle products that provide optical for the second example; we show how feedback flow control can enable particle steering in cheap, handheld micro-fluidic systems using real time vision feedback and routine electro-osmotic actuation. Here we create temporally and spatially varying flow fields that carry all the particles along their desired trajectories. We have demonstrated flow steering of many particles at once both in simulations and in experiments. (Flow control steering for a single yeast cell is shown above.) This system is being further developed to enable sample preparation (remove all but the interesting objects from the sample) and for cell loading for a 'cell clinics' olfactory and bio-chemical sensing system at the University of Maryland.