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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Author: search.filters.author.Bhattacharjee, Sukanta

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Now showing 1 - 4 of 4
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    Storage-Aware Algorithms for Dilution and Mixture Preparation With Flow-Based Lab-on-Chip
    (2020-04-01)
    Bhattacharjee, Sukanta
    ;
    Wille, Robert
    ;
    Huang, Juinn-Dar
    ;
    Bhattacharya, Bhargab B.
    ;
    電子工程學系及電子研究所
    Lab-on-chip (LoC) technology has emerged as one of the major driving forces behind the recent surge in biochemical protocol automation. Dilution and mixture preparation with fluids in a desired ratio, constitute basic steps in sample preparation for which several LoC-based architectures and algorithms are known. The optimization of cost and time for such protocols requires proper sequencing of fluidic mix-and-split steps, and storage-units for holding intermediate-fluids to be reused in the later steps. However, practical design constraints often limit the amount of on-chip storage in microfluidic LoC architectures and thus can badly affect the performance of the algorithms. Consequently, results generated by previous work may not be useful (in the case they require more storage-units 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 mix/split operations or reactant-cost). In this paper, we propose new algorithms for dilution and mixing with continuous-flow-based LoCs that explicitly take care of storage constraints while optimizing reactant-cost and time of sample preparation. We present a symbolic formulation of the problem that captures the degree of freedom in algorithmic steps satisfying the specified storage constraints. Solvers based on Boolean satisfiability are used to achieve the optimization goals. The experimental results show the efficiency and effectiveness of the solution as well as a variety of applications where the proposed methods would prove beneficial.
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    Storage-Aware Sample Preparation Using Flow-Based Microfluidic Labs-on-Chip
    (2018-01-01)
    Bhattacharjee, Sukanta
    ;
    Wille, Robert
    ;
    Huang, Juinn-Dar
    ;
    Bhattacharya, Bhargab B.
    ;
    電子工程學系及電子研究所
    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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    Dilution and Mixing Algorithms for Flow-Based Microfluidic Biochips
    (2017-04-01)
    Bhattacharjee, Sukanta
    ;
    Poddar, Sudip
    ;
    Roy, Sudip
    ;
    Huang, Juinn-Dar
    ;
    Bhattacharya, Bhargab B.
    Albeit sample preparation is well-studied for digital microfluidic biochips, very few prior work addressed this problem in the context of continuous-flow microfluidics from an algorithmic perspective. In the latter class of chips, microvalves and micropumps are used to manipulate on-chip fluid flow through microchannels in order to execute a biochemical protocol. Dilution of a sample fluid is a special case of sample preparation, where only two input reagents (commonly known as sample and buffer) are mixed in a desired volumetric ratio. In this paper, we propose a satisfiability-based dilution algorithm assuming the generalized mixing models supported by an N-segment, continuous-flow, rotary mixer. Given a target concentration and an error limit, the proposed algorithm first minimizes the number of mixing operations, and subsequently, reduces reagent-usage. Simulation results demonstrate that the proposed method outperforms existing dilution algorithms in terms of mixing steps (assay time) and waste production, and compares favorably with respect to reagent-usage (cost) when 4- and 8-segment rotary mixers are used. Next, we propose two variants of an algorithm for handling the open problem of k-reagent mixture-preparation (k >= 3) with an N-segment continuous-flow rotary mixer, and report experimental results to evaluate their performance. A software tool called flow-based sample preparation algorithm has also been developed that can be readily used for running the proposed algorithms.
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    Concentration-Resilient Mixture Preparation with Digital Microfluidic Lab-on-Chip
    (2018-04-01)
    Bhattacharjee, Sukanta
    ;
    Chen, Yi-Ling
    ;
    Huang, Juinn-Dar
    ;
    Bhattacharya, Bhargab B.
    ;
    電子工程學系及電子研究所
    Sample preparation plays a crucial role in almost all biochemical applications, since a predominant portion of biochemical analysis time is associated with sample collection, transportation, and preparation. Many sample-preparation algorithms are proposed in the literature that are suitable for execution on programmable digital microfluidic (DMF) platforms. In most of the existing DMF-based sample-preparation algorithms, a fixed target ratio is provided as input, and the corresponding mixing tree is generated as output. However, in many biochemical applications, target mixtures with exact component proportions may not be needed. From a biochemical perspective, it may be sufficient to prepare a mixture in which the input reagents may lie within a range of concentration factors. The choice of a particular valid ratio, however, strongly impacts solution-preparation cost and time. To address this problem, we propose a concentration-resilient ratioselection method from the input ratio space so that the reactant cost is minimized. We propose an integer linear programming-based method that terminates very fast while producing the optimum solution, considering both uniform and weighted cost of reagents. Experimental results reveal that the proposed method can be used conveniently in tandem with several existing sample-preparation algorithms for improving their performance.