Paper Info
Title
A Multi-Commodity Network Flow Based Routing Algorithm for Paper-Based Digital Microfluidic Biochips
Abstract
ABSTRACTPaper-based digital microfluidic biochips (P-DMFBs) have emerged as a safe, low-cost, and fast-responsive platform for biochemical assays. In P-DMFB, droplet manipulations are executed by the electrowetting technology. In order to enable the electrowetting technology, pattern arrays of electrodes and control lines are coated on paper with a hydrophobic Teflon film and dielectric parylene-C film. Different from traditional DMFBs, the manufacturing of P-DMFBs is efficient and inexpensive since the electrodes and control lines are printed on photo paper with an inkjet printer. Active paper-based hybridized chip (APHC) is a type of P-DMFBs that has open and closed part. APHC enjoys more convenience than common P-DMFBs since it has no need to fabricate and maintain the micro gap between glass and paper chip, which requires highly delicate treatments. However, the pattern rails of electrodes in APHCs are denser than traditional P-DMFBs, which makes existing electrode routing algorithm fail in APHCs. To deal with the challenge in electrode routing of APHCs, this paper proposes a multi-commodity network flow-based routing algorithm, which simultaneously maximizes the routability and minimizes the total wire length of control lines. The multi-commodity flow model can utilize the pin-sharing between electrodes, which can improve routability and reduce the detour of routing lines. Moreover, the activation sequences of electrodes are considered, which guarantees that the bioassay will not be interfered with after pin-sharing. The proposed method achieves a 100% successful routing rate on real-life APHCs while other electrode routing method cannot solve the electrode routing of APHCs successfully.
Year
DOI
Venue
2021
10.1145/3394885.3431611
ASPDAC
Keywords
DocType
ISSN
digital microfluidic, network flow, routing
Conference
2153-6961
ISBN
Citations 
PageRank 
978-1-7281-8057-1
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Nai-Ren Shih100.34
Tsung-Yi Ho25921.63