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Title: An intelligent digital microfluidic system with fuzzy-enhanced feedback for multi-droplet manipulation
Authors: Gao, Jie
Lin, Bingcheng
Liu, Xianming
Chen, Tianlan
Du, Yuguang
Mak, Pui In (麥沛然)
Vai, Mang I (韋孟宇)
Martins, Rui Paulo Da Silva
Issue Date: 28-Nov-2012
Publisher: Royal Society of Chemistry
Citation: Lab on a Chip, Nov 2012, Vol. 3, Issue 13, p. 443-451
Abstract: The complexity of droplet hydrodynamics on a digital microfluidic (DMF) system eventually weakens its potential for application in large-scale chemical/biological micro-reactors. We describe here an intelligent DMF technology to address that intricacy. A wide variety of control-engaged droplet manageability is proposed and demonstrated through the operation of our modular DMF prototype, which comprises: (i) rigid profiling ability of different droplet's hydrodynamics under a real-time trajectory track of droplet-derived capacitance, permitting accurate and autonomous multi-droplet positioning without visual setup and heavy image signal processing; (ii) fuzzy-enhanced controllability saving up to 21% charging time when compared with the classical approach, enhancing the throughput, fidelity and lifetime of the DMF chip, while identifying and renouncing those weakened electrodes deteriorated over time, and (iii) expert manipulability of multi-droplet routings under countermeasure decisions in real time, preventing droplet-to-droplet or task-to-task interference. Altogether, this work exhibits the first modular DMF system with built-in electronic-control software-defined intelligence to enhance the fidelity and reliability of each droplet operation, allowing future manufacturability of a wide range of life science analyses and combinatorial chemical screening applications.
ISSN: 1473-0197
Access: View full-text via DOI

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