Design and Optimization Methods for Pin-Limited and Cyberphysical Digital Microfluidic Biochips

<p>Microfluidic biochips have now come of age, with applications to biomolecular recognition for high-throughput DNA sequencing, immunoassays, and point-of-care clinical diagnostics. In particular, digital microfluidic biochips, which use electrowetting-on-dielectric to manipulate discrete droplets (or "packets of biochemical payload") of picoliter volumes under clock control, are especially promising. The potential applications of biochips include real-time analysis for biochemical reagents, clinical diagnostics, flash chemistry, and on-chip DNA sequencing. The ease of reconfigurability and software-based control in digital microfluidics has motivated research on various aspects of automated chip design and optimization.</p><p>This thesis research is focused on facilitating advances in on-chip bioassays, enhancing the automated use of digital microfluidic biochips, and developing an "intelligent" microfluidic system that has the capability of making on-line re-synthesis while a bioassay is being executed. This thesis includes the concept of a "cyberphysical microfluidic biochip" based on the digital microfluidics hardware platform and on-chip sensing technique. In such a biochip, the control software, on-chip sensing, and the microfluidic operations are tightly coupled. The status of the droplets is dynamically monitored by on-chip sensors. If an error is detected, the control software performs dynamic re-synthesis procedure and error recovery.</p><p>In order to minimize the size and cost of the system, a hardware-assisted error-recovery method, which relies on an error dictionary for rapid error recovery, is also presented. The error-recovery procedure is controlled by a finite-state-machine implemented on a field-programmable gate array (FPGA) instead of a software running on a separate computer. Each state of the FSM represents a possible error that may occur on the biochip; for each of these errors, the corresponding sequence of error-recovery signals is stored inside the memory of the FPGA before the bioassay is conducted. When an error occurs, the FSM transitions from one state to another, and the corresponding control signals are updated. Therefore, by using inexpensive FPGA, a portable cyberphysical system can be implemented.</p><p>In addition to errors in fluid-handling operations, bioassay outcomes can also be erroneous due the uncertainty in the completion time for fluidic operations. Due to the inherent randomness of biochemical reactions, the time required to complete each step of the bioassay is a random variable. To address this issue, a new "operation-interdependence-aware" synthesis algorithm is proposed in this thesis. The start and stop time of each operation are dynamically determined based on feedback from the on-chip sensors. Unlike previous synthesis algorithms that execute bioassays based on pre-determined start and end times of each operation, the proposed method facilitates "self-adaptive" bioassays on cyberphysical microfluidic biochips.</p><p>Another design problem addressed in this thesis is the development of a layout-design algorithm that can minimize the interference between devices on a biochip. A probabilistic model for the polymerase chain reaction (PCR) has been developed; based on the model, the control software can make on-line decisions regarding the number of thermal cycles that must be performed during PCR. Therefore, PCR can be controlled more precisely using cyberphysical integration.</p><p>To reduce the fabrication cost of biochips, yet maintain application flexibility, the concept of a "general-purpose pin-limited biochip" is proposed. Using a graph model for pin-assignment, we develop the theoretical basis and a heuristic algorithm to generate optimized pin-assignment configurations. The associated scheduling algorithm for on-chip biochemistry synthesis has also been developed. Based on the theoretical framework, a complete design flow for pin-limited cyberphysical microfluidic biochips is presented.</p><p>In summary, this thesis research has led to an algorithmic infrastructure and optimization tools for cyberphysical system design and technology demonstrations. The results of this thesis research are expected to enable the hardware/software co-design of a new class of digital microfluidic biochips with tight coupling between microfluidics, sensors, and control software.</p>Dissertatio

Placement and routing for cross-referencing digital microfluidic biochips.

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

Fluigi: an end-to-end software workflow for microfluidic design

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications with implications in health, materials, and sensing. Computational design methodologies allow for increased performance and reliability of these circuits. Major challenges that remain include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of “specify-design-build-test.” I summarize the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow for genetic circuits. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. However, adoption of microfluidics for synthetic biology has been slow due to the expert knowledge and equipment needed to fabricate and control devices. I present an end-to-end workflow for a computer-aided-design (CAD) tool, Fluigi, for designing microfluidic devices and for integrating biological Boolean genetic circuits with microfluidics. The workflow starts with a ``netlist" input describing the connectivity of microfluidic device to be designed, and proceeds through placement, routing, and design rule checking in a process analogous to electronic computer aided design (CAD). The output is an image of the device for printing as a mask for photolithography or for computer numerical control (CNC) machining. I also introduced a second workflow to allocate biological circuits to microfluidic devices and to generate the valve control scheme to enable biological computation on the device. I used the CAD workflow to generate 15 designs including gradient generators, rotary pumps, and devices for housing biological circuits. I fabricated two designs, a gradient generator with CNC machining and a device for computing a biological XOR function with multilayer soft lithography, and verified their functions with dye. My efforts here show a first end-to-end demonstration of an extensible and foundational microfluidic CAD tool from design concept to fabricated device. This work provides a platform that when completed will automatically synthesize high level functional and performance specifications into fully realized microfluidic hardware, control software, and synthetic biological wetware

A Software Toolchain for Physical System Description and Synthesis, and Applications to Microfluidic Design Automation

Microfluidic circuits are currently designed by hand, using a combination of the designer’s domain knowledge and educated intuition to determine unknown design parameters. As no microfluidic circuit design software exists to assist designers, circuits are typically tested by physically constructing them in silico and performing another design iteration should the prototype fail to operate correctly. Similar to how electronic design automation tools revolutionized the digital circuit design process, so too do microfluidic design packages have the potential to increase productivity for microfluidic circuit designers and allow more complex devices to be designed. Two of the primary software engineering problems to be solved in this space relate to design entry and design synthesis. First, the circuit designer requires a programming language to describe the behaviour and properties of the device they wish to build, and a compiler toolchain to convert this description into a model that can then be processed by other software tools. Second, once such a model is constructed, the remaining portions of the design toolchain must be constructed. It is necessary to implement software that can find unknown design parameters automatically to relieve the designer of much of the complexity that goes into creating such a circuit. Furthermore, automated testing and verification tools must be used to simulate the device and check for correctness and safety requirements before the engineer can have confidence in their design. In this thesis I outline work that has been done towards both of these goals. First, I describe a new programming language that has been developed for the purpose of describing and modelling physical systems, including but not limited to microfluidic circuits. This programming language, called “Manifold”, has been implemented following principles and features of modern functional programming languages, as well as drawing inspiration from VHDL and Verilog, the two industry-standard programming languages for EDA. The Manifold high-level language compiler carries out the process of translating a system description into a domain-agnostic intermediate representation. This representation is then passed to a domain-specific backend compiler which can perform further operations on the design, such as creating simulations, performing verification, and generating appropriate output products. Second, I perform a case study with respect to the creation of such a domain-specific backend for the domain of multi-phase microfluidic circuits. The process involved in taking a circuit description from design entry to device specification has a number of significant steps. I discuss in detail these steps with respect to the design of a multi-way droplet generator circuit. Such a circuit is difficult to design because of the behaviour of the key design parameter, the volume of generated droplets. The design goal is for each droplet generator on the device to produce droplets of a certain specified volume. However, the equation relating the properties of a droplet generator to the predicted droplet volume is complex and contains several nonlinearities, making it very difficult to solve by traditional methods. Recent advances in constraint solvers which can reason about nonlinear equations over real-valued terms make it possible to solve this equation efficiently for a given set of design constraints and goals, and produce many feasible specifications for droplet generators that meet the requirements. Another difficulty in designing these circuits is due to interactions between droplet generators. As the produced droplets have a significant hydrodynamic resistance, they affect the behaviour of the circuit by causing perturbations in the flow rates into the droplet generators. This has the potential to alter the volume of droplets that are being produced. Therefore, a means of regulating or controlling the flow rates must be found. I describe a potential solution in the form of a passive element analogous to a capacitor in an electrical circuit. Once an appropriate value for the capacitor is chosen, it remains to verify that it operates correctly under manufacturing variances in fabrication of the device. To perform this verification, a bounded model checker for real-valued differential equations is employed to demonstrate correctness or discover robustness issues. Furthermore, a simulation file for the MapleSim numerical simulation engine is generated in order to perform whole-design tests for further validation. The sequence in which these steps are performed closely follows the concept of “abstraction refinement” in formal methods, in which successively more detailed models are checked and a failure in one step can invoke a previous step with new information, allowing errors to be caught early and introducing the ability to iterate on the design. I describe such a refinement loop in place in the microfluidics backend that integrates these three steps in a coherent design flow, able to synthesize and verify many specifications for a microfluidic circuit, thereby automating a significant portion of the design process. The combination of the Manifold high-level language and microfluidics backend introduces a new design automation toolchain that demonstrates the effectiveness of constraint solvers in the tasks of design synthesis and verification. Further enhancements to the performance and capabilities of these solvers, as well as to the high-level language and backend, will in the future produce a general-purpose design package for microfluidic circuits that will allow for new, complex designs to be created and checked with confidence

MakerFluidics: low cost microfluidics for synthetic biology

Recent advancements in multilayer, multicellular, genetic logic circuits often rely on manual intervention throughout the computation cycle and orthogonal signals for each chemical “wire”. These constraints can prevent genetic circuits from scaling. Microfluidic devices can be used to mitigate these constraints. However, continuous-flow microfluidics are largely designed through artisanal processes involving hand-drawing features and accomplishing design rule checks visually: processes that are also inextensible. Additionally, continuous-flow microfluidic routing is only a consideration during chip design and, once built, the routing structure becomes “frozen in silicon,” or for many microfluidic chips “frozen in polydimethylsiloxane (PDMS)”; any changes to fluid routing often require an entirely new device and control infrastructure. The cost of fabricating and controlling a new device is high in terms of time and money; attempts to reduce one cost measure are, generally, paid through increases in the other. This work has three main thrusts: to create a microfluidic fabrication framework, called MakerFluidics, that lowers the barrier to entry for designing and fabricating microfluidics in a manner amenable to automation; to prove this methodology can design, fabricate, and control complex and novel microfluidic devices; and to demonstrate the methodology can be used to solve biologically-relevant problems. Utilizing accessible technologies, rapid prototyping, and scalable design practices, the MakerFluidics framework has demonstrated its ability to design, fabricate and control novel, complex and scalable microfludic devices. This was proven through the development of a reconfigurable, continuous-flow routing fabric driven by a modular, scalable primitive called a transposer. In addition to creating complex microfluidic networks, MakerFluidics was deployed in support of cutting-edge, application-focused research at the Charles Stark Draper Laboratory. Informed by a design of experiments approach using the parametric rapid prototyping capabilities made possible by MakerFluidics, a plastic blood--bacteria separation device was optimized, demonstrating that the new device geometry can separate bacteria from blood while operating at 275% greater flow rate as well as reduce the power requirement by 82% for equivalent separation performance when compared to the state of the art. Ultimately, MakerFluidics demonstrated the ability to design, fabricate, and control complex and practical microfluidic devices while lowering the barrier to entry to continuous-flow microfluidics, thus democratizing cutting edge technology beyond a handful of well-resourced and specialized labs

Exploring Microfluidic Design Automation: Thin-wall Membrane Regulator

Microfluidics and lab-on-a-chip are a growing technology, influential in many areas of engineering. This project focuses on the necessity for better computer aided design tools for this area. Specifically, it focuses on the automated synthesis of T-junction components with thin-walled membranes for stability. A T-junction is a passive droplet generation component, common in microfluidics which suffers from behavior instability in highly integrated circuits with many components. One way of improving stability is using flexible membranes to mitigate pressure perturbations. This thesis describes the design process of such membranes so that a model can be used to synthesize stable T-junctions. The thesis also discusses Manifold, a software framework for automated synthesis of microfluidic circuits. This is the framework where the design process fits in. To compare the result of the software framework with the analytic model described, physical circuits were fabricated to validate the accuracy of the analytic model and the software. Besides the T-junction, another microfluidics component that was investigated was a “Capillary Electrophoresis Channel”. This component was also investigated with respect to automated synthesis and verification using the Manifold framework, and the details are discussed

Test analysis & fault simulation of microfluidic systems

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