Storage-Aware Sample Preparation Using Flow-Based Microfluidic Labs-on-Chip

Sukanta Bhattacharjee1, Robert Wille2, Juinn-Dar Huang3 and Bhargab B. Bhattacharya4
1Center for Cyber Security, New York University, Abu Dhabi, UAE
sb5638@nyu.edu
2Institute for Integrated Circuits, Johannes Kepler University Linz, 4040 Linz, Austria
robert.wille@jku.at
3Department of Electronics Engineering, National Chiao Tung University, Taiwan
jdhuang@mail.nctu.edu.tw
4Nanotechnology Research Triangle, Indian Statistical Institute, Kolkata
bhargab@isical.ac.in

ABSTRACT


Recent advances in microfluidics have been the major driving force behind the ubiquity of Labs‐on‐Chip (LoC) in biochemical protocol automation. The preparation of dilutions and mixtures of fluids is a basic step in sample preparation for which several algorithms and chip‐architectures are well known. Dilution and mixing are implemented on biochips through a sequence of basic fluid‐mixing and splitting operations performed in certain ratios. These steps are abstracted using a mixing graph. During this process, on‐chip storage‐units are needed to store intermediate fluids to be used later in the sequence. This allows to optimize the reactant‐costs, to reduce the sample‐preparation time, and/or to achieve the desired ratio. However, the number of storage‐units is usually limited in given LoC architectures. Since this restriction is not considered by existing methods for sample preparation, the results that are obtained are often found to be useless (in the case when more storage‐units are required than available) or more expensive than necessary (in the case when storage‐units are available but not used, e.g., to further reduce the number of mixing operations or reactant‐cost). In this paper, we present a storage‐aware algorithm for sample preparation with flow‐based LoCs which addresses these issues. We present a SAT‐based approach to construct a mixing graph that enables the best usage of available storage‐units while optimizing sample‐preparation cost and/or time. Experimental results on several test cases reveal the scope, effectiveness, and the flexibility of the proposed method.



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