9 research outputs found

    Synthesis of Digital Microfluidic Biochips with Reconfigurable Operation Execution

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    Compilation and Synthesis for Fault-Tolerant Digital Microfluidic Biochips

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    Placement and routing for cross-referencing digital microfluidic biochips.

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    Xiao, Zigang."October 2010."Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (leaves 62-66).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.viChapter 1 --- Introduction --- p.1Chapter 1.1 --- Microfluidic Technology --- p.2Chapter 1.1.1 --- Continuous Flow Microfluidic System --- p.2Chapter 1.1.2 --- Digital Microfluidic System --- p.2Chapter 1.2 --- Pin-Constrained Biochips --- p.4Chapter 1.2.1 --- Droplet-Trace-Based Array Partitioning Method --- p.5Chapter 1.2.2 --- Broadcast-addressing Method --- p.5Chapter 1.2.3 --- Cross-Referencing Method --- p.6Chapter 1.2.3.1 --- Electrode Interference in Cross-Referencing Biochips --- p.7Chapter 1.3 --- Computer-Aided Design Techniques for Biochip --- p.8Chapter 1.4 --- Placement Problem in Biochips --- p.8Chapter 1.5 --- Droplet Routing Problem in Cross-Referencing Biochips --- p.11Chapter 1.6 --- Our Contributions --- p.14Chapter 1.7 --- Thesis Organization --- p.15Chapter 2 --- Literature Review --- p.16Chapter 2.1 --- Introduction --- p.16Chapter 2.2 --- Previous Works on Placement --- p.17Chapter 2.2.1 --- Basic Simulated Annealing --- p.17Chapter 2.2.2 --- Unified Synthesis Approach --- p.18Chapter 2.2.3 --- Droplet-Routing-Aware Unified Synthesis Approach --- p.19Chapter 2.2.4 --- Simulated Annealing Using T-tree Representation --- p.20Chapter 2.3 --- Previous Works on Routing --- p.21Chapter 2.3.1 --- Direct-Addressing Droplet Routing --- p.22Chapter 2.3.1.1 --- A* Search Method --- p.22Chapter 2.3.1.2 --- Open Shortest Path First Method --- p.23Chapter 2.3.1.3 --- A Two Phase Algorithm --- p.24Chapter 2.3.1.4 --- Network-Flow Based Method --- p.25Chapter 2.3.1.5 --- Bypassibility and Concession Method --- p.26Chapter 2.3.2 --- Cross-Referencing Droplet Routing --- p.28Chapter 2.3.2.1 --- Graph Coloring Method --- p.28Chapter 2.3.2.2 --- Clique Partitioning Method --- p.30Chapter 2.3.2.3 --- Progressive-ILP Method --- p.31Chapter 2.4 --- Conclusion --- p.32Chapter 3 --- CrossRouter for Cross-Referencing Biochip --- p.33Chapter 3.1 --- Introduction --- p.33Chapter 3.2 --- Problem Formulation --- p.34Chapter 3.3 --- Overview of Our Method --- p.35Chapter 3.4 --- Net Order Computation --- p.35Chapter 3.5 --- Propagation Stage --- p.36Chapter 3.5.1 --- Fluidic Constraint Check --- p.38Chapter 3.5.2 --- Electrode Constraint Check --- p.38Chapter 3.5.3 --- Handling 3-pin net --- p.44Chapter 3.5.4 --- Waste Reservoir --- p.45Chapter 3.6 --- Backtracking Stage --- p.45Chapter 3.7 --- Rip-up and Re-route Nets --- p.45Chapter 3.8 --- Experimental Results --- p.46Chapter 3.9 --- Conclusion --- p.47Chapter 4 --- Placement in Cross-Referencing Biochip --- p.49Chapter 4.1 --- Introduction --- p.49Chapter 4.2 --- Problem Formulation --- p.50Chapter 4.3 --- Overview of the method --- p.50Chapter 4.4 --- Dispenser and Reservoir Location Generation --- p.51Chapter 4.5 --- Solving Placement Problem Using ILP --- p.51Chapter 4.5.1 --- Constraints --- p.53Chapter 4.5.1.1 --- Validity of modules --- p.53Chapter 4.5.1.2 --- Non-overlapping and separation of Modules --- p.53Chapter 4.5.1.3 --- Droplet-Routing length constraint --- p.54Chapter 4.5.1.4 --- Optical detector resource constraint --- p.55Chapter 4.5.2 --- Objective --- p.55Chapter 4.5.3 --- Problem Partition --- p.56Chapter 4.6 --- Pin Assignment --- p.56Chapter 4.7 --- Experimental Results --- p.57Chapter 4.8 --- Conclusion --- p.59Chapter 5 --- Conclusion --- p.60Bibliography --- p.6

    A housekeeping prognostic health management framework for microfluidic systems

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    Micro-Electro-Mechanical Systems (MEMS) and Microfluidics are becoming popular solutions for sensing, diagnostics and control applications. Reliability and validation of function is of increasing importance in the majority of these applications. On-line testing strategies for these devices have the potential to provide real-time condition monitoring information. It is shown that this information can be used to diagnose and prognose the health of the device. This information can also be used to provide an early failure warning system by predicting the remaining useful life. Diagnostic and prognostic outcomes can also be leveraged to improve the reliability, dependability and availability of these devices. This work has delivered a methodology for a “lightweight” prognostics solution for a microfluidic device based on real-time diagnostics. An oscillation based test methodology is used to extract diagnostic information that is processed using a Linear Discriminant Analysis based classifier. This enables the identification of current health based on pre-defined health levels. As the deteriorating device is periodically classified, the rate at which the device degrades is used to predict the devices remaining useful life

    Test analysis & fault simulation of microfluidic systems

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    This work presents a design, simulation and test methodology for microfluidic systems, with particular focus on simulation for test. A Microfluidic Fault Simulator (MFS) has been created based around COMSOL which allows a fault-free system model to undergo fault injection and provide test measurements. A post MFS test analysis procedure is also described.A range of fault-free system simulations have been cross-validated to experimental work to gauge the accuracy of the fundamental simulation approach prior to further investigation and development of the simulation and test procedure.A generic mechanism, termed a fault block, has been developed to provide fault injection and a method of describing a low abstraction behavioural fault model within the system. This technique has allowed the creation of a fault library containing a range of different microfluidic fault conditions. Each of the fault models has been cross-validated to experimental conditions or published results to determine their accuracy.Two test methods, namely, impedance spectroscopy and Levich electro-chemical sensors have been investigated as general methods of microfluidic test, each of which has been shown to be sensitive to a multitude of fault. Each method has successfully been implemented within the simulation environment and each cross-validated by first-hand experimentation or published work.A test analysis procedure based around the Neyman-Pearson criterion has been developed to allow a probabilistic metric for each test applied for a given fault condition, providing a quantitive assessment of each test. These metrics are used to analyse the sensitivity of each test method, useful when determining which tests to employ in the final system. Furthermore, these probabilistic metrics may be combined to provide a fault coverage metric for the complete system.The complete MFS method has been applied to two system cases studies; a hydrodynamic “Y” channel and a flow cytometry system for prognosing head and neck cancer.Decision trees are trained based on the test measurement data and fault conditions as a means of classifying the systems fault condition state. The classification rules created by the decision trees may be displayed graphically or as a set of rules which can be loaded into test instrumentation. During the course of this research a high voltage power supply instrument has been developed to aid electro-osmotic experimentation and an impedance spectrometer to provide embedded test

    An Outlook on Design Technologies for Future Integrated Systems

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    The economic and social demand for ubiquitous and multifaceted electronic systems-in combination with the unprecedented opportunities provided by the integration of various manufacturing technologies-is paving the way to a new class of heterogeneous integrated systems, with increased performance and connectedness and providing us with gateways to the living world. This paper surveys design requirements and solutions for heterogeneous systems and addresses design technologies for realizing them

    Micro- and Nanofluidics for Bionanoparticle Analysis

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    Bionanoparticles such as microorganisms and exosomes are recoganized as important targets for clinical applications, food safety, and environmental monitoring. Other nanoscale biological particles, includeing liposomes, micelles, and functionalized polymeric particles are widely used in nanomedicines. The recent deveopment of microfluidic and nanofluidic technologies has enabled the separation and anslysis of these species in a lab-on-a-chip platform, while there are still many challenges to address before these analytical tools can be adopted in practice. For example, the complex matrices within which these species reside in create a high background for their detection. Their small dimension and often low concentration demand creative strategies to amplify the sensing signal and enhance the detection speed. This Special Issue aims to recruit recent discoveries and developments of micro- and nanofluidic strategies for the processing and analysis of biological nanoparticles. The collection of papers will hopefully bring out more innovative ideas and fundamental insights to overcome the hurdles faced in the separation and detection of bionanoparticles
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