| Title | A Network-Flow-Based Optimal Sample Preparation Algorithm for Digital Microfluidic Biochips |
| Author | *Trung Anh Dinh, Shigeru Yamashita (Ritsumeikan University, Japan), Tsung-Yi Ho (National Cheng Kung University, Taiwan) |
| Page | pp. 225 - 230 |
| Keyword | digital microfluidic biochips, sample preparation, minimum-cost maximum-flow |
| Abstract | Sample preparation, which is a front-end process to produce droplets of the desired target concentrations from input reagents, plays a pivotal role in every assays, laboratories, and applications in biomedical engineering and life science. The consumption of sample/buffer/waste is usually used to evaluate the effectiveness of a sample preparation process. In this paper, we present the first optimal sample preparation algorithm based on a minimum-cost maximum-flow model. By using the proposed model, we can obtain both the optimal cost of sample and buffer usage and the waste amount even for multiple-target concentrations. Experiments demonstrate that we can consistently achieve much better results not only in the consumption of sample and buffer but also the waste amount when compared with all the state-of-the-art of the previous approaches. |
| Slides |
| Title | Exploring Speed and Energy Tradeoffs in Droplet Transport for Digital Microfluidic Biochips |
| Author | Johnathan Fiske, *Daniel Grissom, Philip Brisk (University of California, Riverside, U.S.A.) |
| Page | pp. 231 - 237 |
| Keyword | Microfluidics, Cyber-Physical System, Droplet Transport |
| Abstract | This paper transforms the problem of droplet
routing for digital microfluidic biochips (DMFBs) from the
discrete into the continuous domain, based on the observation
that droplet transport velocity is a function of the actuation
voltage applied to electrodes that control the devices. A new
formulation of the DMFB droplet routing problem is
introduced for the continuous domain, which attempts to
minimize total energy consumption while meeting a timing
constraint. Henceforth, DMFBs should be viewed as continuous,
highly integrated cyber-physical systems that interact with and
manipulate physical quantities, as opposed to inherently
discrete and fully synchronized devices. |
| Slides |
| Title | Wash Optimization for Cross-Contamination Removal in Flow-Based Microfluidic Biochips |
| Author | Kai Hu (Duke University, U.S.A.), *Tsung-Yi Ho (National Cheng Kung University, Taiwan), Krishnendu Chakrabarty (Duke University, U.S.A.) |
| Page | pp. 244 - 249 |
| Keyword | wash optimization, flow-based biochip, cross-contamination |
| Abstract | Recent advances in flow-based microfluidics have enabled the emergence of biochemistry-on-a-chip as a new paradigm in drug discovery and point-of-care disease diagnosis. However, these applications in biochemistry require high precision to avoid erroneous assay outcomes, and therefore are vulnerable to contamination between two fluidic flows with different biochemistries. Moreover, to wash contaminated sites, the buffer solution in flow-based biochips has to be guided along pre-etched channel networks. This constraint makes washing in flow-based microfluidics even harder. In this paper, we propose the first approach for automated wash optimization for contamination removal in flow-based microfluidic biochips. The proposed approach targets the generation of washing pathways to clean all contaminated microchannels with minimum execution time. A path dictionary is first established by pre-searching physically implementable paths in a given chip layout. When wash targets and occupied microchannels are defined, the proposed methods determine an optimized path set with the least washing time by calculating the priorities of wash targets. Two fabricated biochips are used to evaluate the proposed washing method. Compared to an ad hoc baseline method, the proposed approach leads to more efficient washing in all cases. |
| Slides |