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Error recovery in a micro-electrode-dot-array digital microfluidic biochip

Published: 07 November 2016 Publication History

Abstract

A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet volume in a fine-grained manner; (ii) the lack of integrated sensors for real-time detection; (iii) the need for special fabrication processes and the associated reliability/yield concerns. To overcome the above problems, DMFBs based on a micro-electrode-dot-array (MEDA) architecture have been proposed recently, and droplet manipulation on these devices has been experimentally demonstrated. Errors are likely to occur due to defects, chip degradation, and the lack of precision inherent in biochemical experiments. Therefore, an efficient error-recovery strategy is essential to ensure the correctness of assays executed on MEDA biochips. By exploiting MEDA-specific advances in droplet sensing, we present a novel error-recovery technique to dynamically reconfigure the biochip using real-time data provided by on-chip sensors. Local recovery strategies based on probabilistic-timed-automata are presented for various types of errors. A control flow is also proposed to connect local recovery procedures with global error recovery for the complete bioassay. Laboratory experiments using a fabricated MEDA chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three analytical chemistry benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy.

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          2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
          Nov 2016
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          Published: 07 November 2016

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          • (2023)Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA BiochipsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.319480842:4(1212-1222)Online publication date: Apr-2023
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