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Journal articles on the topic 'Microfluidic biochips'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Roy, Pushpita, and Ansuman Banerjee. "A Framework for Validation of Synthesized MicroElectrode Dot Array Actuations for Digital Microfluidic Biochips." ACM Transactions on Design Automation of Electronic Systems 26, no. 6 (July 30, 2021): 1–36. http://dx.doi.org/10.1145/3460437.

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Digital Microfluidics is an emerging technology for automating laboratory procedures in biochemistry. With more and more complex biochemical protocols getting mapped to biochip devices and microfluidics receiving a wide adoption, it is becoming indispensable to develop automated tools and synthesis platforms that can enable a smooth transformation from complex cumbersome benchtop laboratory procedures to biochip execution. Given an informal/semi-formal assay description and a target microfluidic grid architecture on which the assay has to be implemented, a synthesis tool typically translates the high-level assay operations to low-level actuation sequences that can drive the assay realization on the grid. With more and more complex biochemical assay protocols being taken up for synthesis and biochips supporting a wider variety of operations (e.g., MicroElectrode Dot Arrays (MEDAs)), the task of assay synthesis is getting intricately complex. Errors in the synthesized assay descriptions may have undesirable consequences in assay operations, leading to unacceptable outcomes after execution on the biochips. In this work, we focus on the challenge of examining the correctness of synthesized protocol descriptions, before they are taken up for realization on a microfluidic biochip. In particular, we take up a protocol description synthesized for a MEDA biochip and adopt a formal analysis method to derive correctness proofs or a violation thereof, pointing to the exact operation in the erroneous translation. We present experimental results on a few bioassay protocols and show the utility of our framework for verifiable protocol synthesis.

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2

Kitagawa, Daiki, Dieu Quang Nguyen, Trung Anh Dinh, and Shigeru Yamashita. "Graph-Covering-Based Architectural Synthesis for Programmable Digital Microfluidic Biochips." International Journal of Biomedical and Clinical Engineering 6, no. 2 (July 2017): 33–45. http://dx.doi.org/10.4018/ijbce.2017070103.

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Digital microfluidic technology has been extensively applied in various biomedical fields. Different from application-specific biochips, a programmable design has several advantages such as dynamic reconfigurability and general applicability. Basically, a programmable biochip divides the chip into several virtual modules. However, in the previous design, a virtual module can execute only one operation at a time. In this paper, the authors propose a new multi-functional module for programmable digital microfluidic biochips, which can execute two operations simultaneously. Moreover, they also propose a binding and scheduling algorithm for programmable biochips, which is motivated from a graph-covering problem. Experiment demonstrates that their algorithm can reduce the completion time of the applications compared with the previous approaches.

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3

Huang, Xing, Tsung-Yi Ho, Wenzhong Guo, Bing Li, Krishnendu Chakrabarty, and Ulf Schlichtmann. "Computer-aided Design Techniques for Flow-based Microfluidic Lab-on-a-chip Systems." ACM Computing Surveys 54, no. 5 (June 2021): 1–29. http://dx.doi.org/10.1145/3450504.

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As one of the most promising lab-on-a-chip systems, flow-based microfluidic biochips are being increasingly used for automatically executing various laboratory procedures in biology and biochemistry, such as enzyme-linked immunosorbent assay, point-of-care diagnosis, and so on. As manufacturing technology advances, the characteristic dimensions of biochip systems keep shrinking, and tens of thousands of microvalves can now be integrated into a coin-sized microfluidic platform, making the conventional manual-based chip design no longer applicable. Accordingly, computer-aided design (CAD) of microfluidics has attracted considerable research interest in the EDA community over the past decade. This review article presents recent advances in the design automation of biochips, involving CAD techniques for architectural synthesis, wash optimization, testing, fault diagnosis, and fault-tolerant design. With the help of these CAD tools, chip designers can be released from the burden of complex, large-scale design tasks. Meanwhile, new chip architectures can be explored automatically to open new doors to meet requirements from future large-scale biological experiments and medical diagnosis. We discuss key trends and directions for future research that are related to enable microfluidics to reach its full potential, thus further advancing the development and progression of the microfluidics industry.

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4

Wan, Chaowei, Xiaodao Chen, and Dongbo Liu. "A Multi-Objective-Driven Placement Technique for Digital Microfluidic Biochips." Journal of Circuits, Systems and Computers 28, no. 05 (May 2019): 1950076. http://dx.doi.org/10.1142/s0218126619500762.

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Microfluidic biochips are extensively utilized in biochemistry procedures due to their low cost, high precision and efficiency when compared to traditional laboratory procedures. Recent, computer-aided design (CAD) techniques enable a high performance in digital microfluidic biochip design. A key part in digital microfluidic biochip CAD design is the biochip placement procedure which determines the physical location for biological reactions during the physical design. For the biochip physical design, multiple objects need to be considered, such as the size of the chip and the total operation time. In this paper, a multi-objective optimization is proposed based on Markov decision processes (MDPs). The proposed method is evaluated on a set of standard biochip benchmarks. Compared to existing works, experimental results show that the total operation time, the capacity for routing and the chip size can be optimized simultaneously.

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5

Ibrahim, Mohamed, and Krishnendu Chakrabarty. "Digital-Microfluidic Biochips." Computer 49, no. 6 (June 2016): 8–9. http://dx.doi.org/10.1109/mc.2016.187.

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6

Narayanamurthy, Vigneswaran, Tze Lee, Al’aina Khan, Fahmi Samsuri, Khairudin Mohamed, Hairul Hamzah, and Madia Baharom. "Pipette Petri Dish Single-Cell Trapping (PP-SCT) in Microfluidic Platforms: A Passive Hydrodynamic Technique." Fluids 3, no. 3 (July 24, 2018): 51. http://dx.doi.org/10.3390/fluids3030051.

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Microfluidics-based biochips play a vital role in single-cell research applications. Handling and positioning of single cells at the microscale level are an essential need for various applications, including genomics, proteomics, secretomics, and lysis-analysis. In this article, the pipette Petri dish single-cell trapping (PP-SCT) technique is demonstrated. PP-SCT is a simple and cost-effective technique with ease of implementation for single cell analysis applications. In this paper a wide operation at different fluid flow rates of the novel PP-SCT technique is demonstrated. The effects of the microfluidic channel shape (straight, branched, and serpent) on the efficiency of single-cell trapping are studied. This article exhibited passive microfluidic-based biochips capable of vertical cell trapping with the hexagonally-positioned array of microwells. Microwells were 35 μm in diameter, a size sufficient to allow the attachment of captured cells for short-term study. Single-cell capture (SCC) capabilities of the microfluidic-biochips were found to be improving from the straight channel, branched channel, and serpent channel, accordingly. Multiple cell capture (MCC) was on the order of decreasing from the straight channel, branch channel, and serpent channel. Among the three designs investigated, the serpent channel biochip offers high SCC percentage with reduced MCC and NC (no capture) percentage. SCC was around 52%, 42%, and 35% for the serpent, branched, and straight channel biochips, respectively, for the tilt angle, θ values were between 10–15°. Human lung cancer cells (A549) were used for characterization. Using the PP-SCT technique, flow rate variations can be precisely achieved with a flow velocity range of 0.25–4 m/s (fluid channel of 2 mm width and 100 µm height). The upper dish (UD) can be used for low flow rate applications and the lower dish (LD) for high flow rate applications. Passive single-cell analysis applications will be facilitated using this method.

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7

Alistar, Mirela. "Mobile Microfluidics." Bioengineering 6, no. 1 (January 3, 2019): 5. http://dx.doi.org/10.3390/bioengineering6010005.

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Microfluidics platforms can program small amounts of fluids to execute a bio-protocol, and thus, can automate the work of a technician and also integrate a large part of laboratory equipment. Although most microfluidic systems have considerably reduced the size of a laboratory, they are still benchtop units, of a size comparable to a desktop computer. In this paper, we argue that achieving true mobility in microfluidics would revolutionize the domain by making laboratory services accessible during traveling or even in daily situations, such as sport and outdoor activities. We review the existing efforts to achieve mobility in microfluidics, and we discuss the conditions mobile biochips need to satisfy. In particular, we show how we adapted an existing biochip for mobile use, and we present the results when using it during a train ride. Based on these results and our systematic discussion, we identify the challenges that need to be overcome at technical, usability and social levels. In analogy to the history of computing, we make some predictions on the future of mobile biochips. In our vision, mobile biochips will disrupt how people interact with a wide range of healthcare processes, including medical testing and synthesis of on-demand medicine.

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8

Zhang, Ling, Jun Jin Mei, Bo Wu Yan, and Qin Gao. "A Test Droplets Dispensing Solution for Digital Microfluidic Biochip Parallel Testing." Key Engineering Materials 609-610 (April 2014): 670–74. http://dx.doi.org/10.4028/www.scientific.net/kem.609-610.670.

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Digital microfluidic Biochips are widely used on safety-critical biomedical applications, and dependability is an essential attribute for them. To reduce dispensing time, a new test droplets dispensing solution for digital microfluidic biochip parallel testing is proposed in the paper, where multiple test droplets are allotted to the limited test dispensing sources to transmit them to the corresponding test target. The goal is minimizing the dispensing time, and then reduces the system testing time. Even thought the problem is shown to be NP-complete, it can be solved exactly for practical instances using integer linear programming (ILP). The experimental results demonstrate that optimal solutions to the test droplets dispensing problem in microfluidic biochip parallel testing are indeed feasible.

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9

Lee, Moo-Yeal, Aravind Srinivasan, Bosung Ku, and Jonathan S. Dordick. "Multienzyme catalysis in microfluidic biochips." Biotechnology and Bioengineering 83, no. 1 (May 5, 2003): 20–28. http://dx.doi.org/10.1002/bit.10642.

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10

Chiu, Yi-Lung, Ruchi Ashok Kumar Yadav, Hong-Yuan Huang, Yi-Wen Wang, and Da-Jeng Yao. "Unveiling the Potential of Droplet Generation, Sorting, Expansion, and Restoration in Microfluidic Biochips." Micromachines 10, no. 11 (November 6, 2019): 756. http://dx.doi.org/10.3390/mi10110756.

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Microfluidic biochip techniques are prominently replacing conventional biochemical analyzers by the integration of all functions necessary for biochemical analysis using microfluidics. The microfluidics of droplets offer exquisite control over the size of microliter samples to satisfy the requirements of embryo culture, which might involve a size ranging from picoliter to nanoliter. Polydimethylsiloxane (PDMS) is the mainstream material for the fabrication of microfluidic devices due to its excellent biocompatibility and simplicity of fabrication. Herein, we developed a microfluidic biomedical chip on a PDMS substrate that integrated four key functions—generation of a droplet of an emulsion, sorting, expansion and restoration, which were employed in a mouse embryo system to assess reproductive medicine. The main channel of the designed chip had width of 1200 μm and height of 500 μm. The designed microfluidic chips possessed six sections—cleaved into three inlets and three outlets—to study the key functions with five-day embryo culture. The control part of the experiment was conducted with polystyrene (PS) beads (100 μm), the same size as the murine embryos, for the purpose of testing. The outcomes of our work illustrate that the rate of success of the static droplet culture group (87.5%) is only slightly less than that of a conventional group (95%). It clearly demonstrates that a droplet-based microfluidic system can produce a droplet in a volume range from picoliter to nanoliter.

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11

Chang, Yaw-Jen, Yeon Pun Chang, and Kai Yuan Cheng. "Operation Principle and Simulation of Loop-Type Microfluidic Biochips." Materials Science Forum 505-507 (January 2006): 649–54. http://dx.doi.org/10.4028/www.scientific.net/msf.505-507.649.

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Biochip is an emerging technology and has evoked great research interests in recent years. In this paper, a novel air-driven loop-type microfluidic biochip was investigated. Differing from conventional micro channels, this chip has a micro loop-channel and 3 sets of driving conduits with valveless design in their intersections so that the microfluid can be driven smoothly in unidirectional circular movements. The driving efficiency reaches the highest if the entry angle of driving conduits is in the tangent direction of the loop-channel. However, the smaller the included angle, the impact area the larger, leading to comparatively serious reflow phenomenon. Furthermore, the microfluid can be controlled to stop almost instantaneously in the loop segment. Therefore, this loop-type biochip is suitable for biochemical reactions under repeated multiple temperature operations such as polymerase chain reaction. A full circular movement completes a cycle of PCR amplification. Besides, this biochip has its merits including simpler chip design, shorter channel length, and flexible controllability for biochemical reactions.

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12

Ho, Tsung-Yi. "Design Automation for Digital Microfluidic Biochips." IPSJ Transactions on System LSI Design Methodology 7 (2014): 16–26. http://dx.doi.org/10.2197/ipsjtsldm.7.16.

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13

Paşaniuc, Bogdan, Robert Garfinkel, Ion Măndoiu, and Alex Zelikovsky. "Optimal Testing of Digital Microfluidic Biochips." INFORMS Journal on Computing 23, no. 4 (November 2011): 518–29. http://dx.doi.org/10.1287/ijoc.1100.0422.

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14

Chang, Chin Lung, Weij Hong Ju, Ching Liang Liou, Jik Chang Leong, and Lung Ming Fu. "Rapid Microfluidc Biochips Fabrication by Femtosecond Laser on Glass Substrate." Key Engineering Materials 483 (June 2011): 359–63. http://dx.doi.org/10.4028/www.scientific.net/kem.483.359.

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This paper uses a femtosecond laser scriber to perform the direct-writing ablation of glass substrate for the development of microfluidic biochips. The surface quality of the ablated microchannels was examined by scanning electron microscopy (SEM) and atomic force microscopy (AFM) measurement techniques. The developed femtosecond laser ablation system provides a versatile and economic approach for the fabrication of glass-base microfluidic chips. In the laser writing process, the desired microfluidic patterns are designed using commercial computer software and are then transferred to the laser scriber to ablate the trenches. The results show that a very smooth channel wall can be achieved through the annealing process at the temperature 650°C and 5 hours. The system provides an economic and powerful means of rapid glass microfluidic biochips development.

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15

Narayanamurthy, Vigneswaran, Sairam Nagarajan, Al'aina Yuhainis Firus Khan, Fahmi Samsuri, and T. M. Sridhar. "Microfluidic hydrodynamic trapping for single cell analysis: mechanisms, methods and applications." Analytical Methods 9, no. 25 (2017): 3751–72. http://dx.doi.org/10.1039/c7ay00656j.

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16

Thuenauer, Roland, Enrique Rodriguez-Boulan, and Winfried Römer. "Microfluidic approaches for epithelial cell layer culture and characterisation." Analyst 139, no. 13 (2014): 3206–18. http://dx.doi.org/10.1039/c4an00056k.

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17

Mohammadzadeh, Naser, Robert Wille, and Oliver Keszocze. "Efficient One-pass Synthesis for Digital Microfluidic Biochips." ACM Transactions on Design Automation of Electronic Systems 26, no. 4 (April 2021): 1–21. http://dx.doi.org/10.1145/3446880.

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Digital microfluidics biochips are a promising emerging technology that provides fluidic experimental capabilities on a chip (i.e., following the lab-on-a-chip paradigm). However, the design of such biochips still constitutes a challenging task that is usually tackled by multiple individual design steps, such as binding, scheduling, placement, and routing. Performing these steps consecutively may lead to design gaps and infeasible results. To address these shortcomings, the concept of one-pass design for digital microfluidics biochips has recently been proposed—a holistic approach avoiding the design gaps by considering the whole synthesis process as large. But implementations of this concept available thus far suffer from either high computational effort or costly results. In this article, we present an efficient one-pass solution that is runtime efficient (i.e., rarely needing more than a second to successfully synthesize a design) while, at the same time, producing better results than previously published heuristic approaches. Experimental results confirm the benefits of the proposed solution and allow for realizing really large assays composed of thousands of operations in reasonable runtime.

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18

Liu, Robin Hui, Kilian Dill, H. Sho Fuji, and Andy McShea. "Integrated microfluidic biochips for DNA microarray analysis." Expert Review of Molecular Diagnostics 6, no. 2 (March 2006): 253–61. http://dx.doi.org/10.1586/14737159.6.2.253.

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19

Davids, Daniel, Siddhartha Datta, Arindam Mukherjee, Bharat Joshi, and Arun Ravindran. "Multiple fault diagnosis in digital microfluidic biochips." ACM Journal on Emerging Technologies in Computing Systems 2, no. 4 (October 2006): 262–76. http://dx.doi.org/10.1145/1216396.1216398.

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20

Shang Tsung, Yu, and Ho Tsung-Yi. "Chip-Level Design for Digital Microfluidic Biochips." International Journal of Automation and Smart Technology 4, no. 4 (December 1, 2014): 202–7. http://dx.doi.org/10.5875/ausmt.v4i4.770.

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21

Mir, Kalim U. "Biochips: from chipped gels to microfluidic CDs." Drug Discovery Today 3, no. 11 (November 1998): 485–86. http://dx.doi.org/10.1016/s1359-6446(98)01263-x.

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22

Ali, Sk Subidh, Mohamed Ibrahim, Jeyavijayan Rajendran, Ozgur Sinanoglu, and Krishnendu Chakrabarty. "Supply-Chain Security of Digital Microfluidic Biochips." Computer 49, no. 8 (August 2016): 36–43. http://dx.doi.org/10.1109/mc.2016.224.

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23

Luo, Yan, Krishnendu Chakrabarty, and Tsung-Yi Ho. "Error Recovery in Cyberphysical Digital Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 32, no. 1 (January 2013): 59–72. http://dx.doi.org/10.1109/tcad.2012.2211104.

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24

Grissom, Daniel T., and Philip Brisk. "Fast Online Synthesis of Digital Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 33, no. 3 (March 2014): 356–69. http://dx.doi.org/10.1109/tcad.2013.2290582.

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25

O'neal, Kenneth, Daniel Grissom, and Philip Brisk. "Resource-Constrained Scheduling for Digital Microfluidic Biochips." ACM Journal on Emerging Technologies in Computing Systems 14, no. 1 (March 13, 2018): 1–26. http://dx.doi.org/10.1145/3093930.

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26

Ali, Sk Subidh, Mohamed Ibrahim, Ozgur Sinanoglu, Krishnendu Chakrabarty, and Ramesh Karri. "Security Assessment of Cyberphysical Digital Microfluidic Biochips." IEEE/ACM Transactions on Computational Biology and Bioinformatics 13, no. 3 (May 1, 2016): 445–58. http://dx.doi.org/10.1109/tcbb.2015.2509991.

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27

Shayan, Mohammed, Sukanta Bhattacharjee, Jack Tang, Krishnendu Chakrabarty, and Ramesh Karri. "Bio-Protocol Watermarking on Digital Microfluidic Biochips." IEEE Transactions on Information Forensics and Security 14, no. 11 (November 2019): 2901–15. http://dx.doi.org/10.1109/tifs.2019.2907185.

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28

Su, Fei, and Krishnendu Chakrabarty. "High-level synthesis of digital microfluidic biochips." ACM Journal on Emerging Technologies in Computing Systems 3, no. 4 (January 2008): 1–32. http://dx.doi.org/10.1145/1324177.1324178.

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29

Ahmadi, Ali, Matthew D. Buat, and Mina Hoorfar. "Microdroplet evaporation in closed digital microfluidic biochips." Journal of Micromechanics and Microengineering 23, no. 4 (February 14, 2013): 045001. http://dx.doi.org/10.1088/0960-1317/23/4/045001.

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30

Tang, Jack, Mohamed Ibrahim, Krishnendu Chakrabarty, and Ramesh Karri. "Secure Randomized Checkpointing for Digital Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 37, no. 6 (June 2018): 1119–32. http://dx.doi.org/10.1109/tcad.2017.2748030.

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31

Tang, Jack, Mohamed Ibrahim, Krishnendu Chakrabarty, and Ramesh Karri. "Toward Secure and Trustworthy Cyberphysical Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 38, no. 4 (April 2019): 589–603. http://dx.doi.org/10.1109/tcad.2018.2855132.

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32

LIU, ROBIN H., JIANING YANG, RALF LENIGK, JUSTIN BONANNO, FREDERIC ZENHAUSERN, and PIOTR GRODZINSKI. "FULLY INTEGRATED MICROFLUIDIC BIOCHIPS FOR DNA ANALYSIS." International Journal of Computational Engineering Science 04, no. 02 (June 2003): 145–50. http://dx.doi.org/10.1142/s1465876303000818.

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33

Maftei, Elena, Paul Pop, and Jan Madsen. "Routing-based synthesis of digital microfluidic biochips." Design Automation for Embedded Systems 16, no. 1 (March 2012): 19–44. http://dx.doi.org/10.1007/s10617-012-9083-0.

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34

Ibrahim, Mohamed, and Krishnendu Chakrabarty. "Cyber–Physical Digital-Microfluidic Biochips: Bridging the Gap Between Microfluidics and Microbiology." Proceedings of the IEEE 106, no. 9 (September 2018): 1717–43. http://dx.doi.org/10.1109/jproc.2017.2759251.

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35

Shukla, Vineeta, Fawnizu Hussin, Nor Hamid, and Noohul Zain Ali. "Advances in Testing Techniques for Digital Microfluidic Biochips." Sensors 17, no. 8 (July 27, 2017): 1719. http://dx.doi.org/10.3390/s17081719.

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36

Soo Ko, Jong, Hyun C. Yoon, Haesik Yang, Hyeon-Bong Pyo, Kwang Hyo Chung, Sung Jin Kim, and Youn Tae Kim. "A polymer-based microfluidic device for immunosensing biochips." Lab on a Chip 3, no. 2 (2003): 106. http://dx.doi.org/10.1039/b301794j.

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37

Read, Timothy D., Rosemary S. Turingan, Christopher Cook, Heidi Giese, Ulrich Hans Thomann, Catherine C. Hogan, Eugene Tan, and Richard F. Selden. "Rapid Multi-Locus Sequence Typing Using Microfluidic Biochips." PLoS ONE 5, no. 5 (May 12, 2010): e10595. http://dx.doi.org/10.1371/journal.pone.0010595.

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Bhattacharjee, Sukanta, Debasis Mitra, and Bhargab B. Bhattacharya. "Robust In-Field Testing of Digital Microfluidic Biochips." ACM Journal on Emerging Technologies in Computing Systems 14, no. 1 (March 13, 2018): 1–17. http://dx.doi.org/10.1145/3123586.

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Wille, Robert, Oliver Keszocze, Rolf Drechsler, Tobias Boehnisch, and Alexander Kroker. "Scalable One-Pass Synthesis for Digital Microfluidic Biochips." IEEE Design & Test 32, no. 6 (December 2015): 41–50. http://dx.doi.org/10.1109/mdat.2015.2455344.

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Ibrahim, Mohamed, and Krishnendu Chakrabarty. "Efficient Error Recovery in Cyberphysical Digital-Microfluidic Biochips." IEEE Transactions on Multi-Scale Computing Systems 1, no. 1 (January 1, 2015): 46–58. http://dx.doi.org/10.1109/tmscs.2015.2478457.

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41

Schneider, Alexander, Paul Pop, and Jan Madsen. "Pin-count reduction for continuous flow microfluidic biochips." Microsystem Technologies 24, no. 1 (April 6, 2017): 483–94. http://dx.doi.org/10.1007/s00542-017-3401-1.

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Shayan, Mohammed, Sukanta Bhattacharjee, Yong-Ak Song, Krishnendu Chakrabarty, and Ramesh Karri. "Toward Secure Microfluidic Fully Programmable Valve Array Biochips." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 27, no. 12 (December 2019): 2755–66. http://dx.doi.org/10.1109/tvlsi.2019.2924915.

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43

Holzer, Julianna, John Wu, Yi He, Mingyang Ma, Yuan Xing, Jose Oberholzer, and Yong Wang. "Application of Microfluidic Biochips for Human Islet Transplantation." OBM Transplantation 2, no. 4 (October 10, 2018): 1. http://dx.doi.org/10.21926/obm.transplant.1804034.

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44

Poddar, Sudip, Sukanta Bhattacharjee, Shao-Yun Fang, Tsung-Yi Ho, and B. B. Bhattacharya. "Demand-Driven Multi-Target Sample Preparation on Resource-Constrained Digital Microfluidic Biochips." ACM Transactions on Design Automation of Electronic Systems 27, no. 1 (January 31, 2022): 1–21. http://dx.doi.org/10.1145/3474392.

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Microfluidic lab-on-chips offer promising technology for the automation of various biochemical laboratory protocols on a minuscule chip. Sample preparation (SP) is an essential part of any biochemical experiments, which aims to produce dilution of a sample or a mixture of multiple reagents in a certain ratio. One major objective in this area is to prepare dilutions of a given fluid with different concentration factors, each with certain volume, which is referred to as the demand-driven multiple-target (DDMT) generation problem. SP with microfluidic biochips requires proper sequencing of mix-split steps on fluid volumes and needs storage units to save intermediate fluids while producing the desired target ratio. The performance of SP depends on the underlying mixing algorithm and the availability of on-chip storage, and the latter is often limited by the constraints imposed during physical design. Since DDMT involves several target ratios, solving it under storage constraints becomes even harder. Furthermore, reduction of mix-split steps is desirable from the viewpoint of accuracy of SP, as every such step is a potential source of volumetric split error. In this article, we propose a storage-aware DDMT algorithm that reduces the number of mix-split operations on a digital microfluidic lab-on-chip. We also present the layout of the biochip with -storage cells and their allocation technique for . Simulation results reveal the superiority of the proposed method compared to the state-of-the-art multi-target SP algorithms.

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45

Zaugg, Frank G., and Peter Wagner. "Drop-on-Demand Printing of Protein Biochip Arrays." MRS Bulletin 28, no. 11 (November 2003): 837–42. http://dx.doi.org/10.1557/mrs2003.233.

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AbstractProtein biochips have recently gained a lot of attention as bioanalytical tools in the life sciences. The creation of such biochips has been made possible by the integration of scientific approaches and methodologies in microfabrication, organic interface chemistry, protein engineering, detection physics, and—last but not least—advances in microarrays and microfluidic dispensing technologies. This article reviews some of the current drop-on-demand technologies developed for printing biomolecular arrays, with an emphasis on proteins and the technical challenges associated with them.

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DINH, Trung Anh, Shigeru YAMASHITA, Tsung-Yi HO, and Yuko HARA-AZUMI. "Clique-Based Architectural Synthesis of Flow-Based Microfluidic Biochips." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A, no. 12 (2013): 2668–79. http://dx.doi.org/10.1587/transfun.e96.a.2668.

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Chakrabarty, K. "Design Automation and Test Solutions for Digital Microfluidic Biochips." IEEE Transactions on Circuits and Systems I: Regular Papers 57, no. 1 (January 2010): 4–17. http://dx.doi.org/10.1109/tcsi.2009.2038976.

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Xiao, Zigang, and Evangeline F. Y. Young. "Placement and Routing for Cross-Referencing Digital Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 30, no. 7 (July 2011): 1000–1010. http://dx.doi.org/10.1109/tcad.2011.2113730.

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Luo, Yan, and Krishnendu Chakrabarty. "Design of Pin-Constrained General-Purpose Digital Microfluidic Biochips." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 32, no. 9 (September 2013): 1307–20. http://dx.doi.org/10.1109/tcad.2013.2260192.

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Tsun-Ming Tseng, Bing Li, Ulf Schlichtmann, and Tsung-Yi Ho. "Storage and Caching: Synthesis of Flow-Based Microfluidic Biochips." IEEE Design & Test 32, no. 6 (December 2015): 69–75. http://dx.doi.org/10.1109/mdat.2015.2492473.

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