Abstract—This paper describes a computational approach to designing a digital microfluidic system (DMFS) that can be rapidly reconfigured for new biochemical analyses. Such a “lab-on-a-chip” system for biochemical analysis, based on electrowetting or dielectrophoresis, must coordinate the motions of discrete droplets or biological cells using a planar array of electrodes. The authors have earlier introduced a layout-based system and demonstrated its flexibility through simulation, including the system’s ability to perform multiple assays simultaneously. Since array-layout design and droplet-routing strategies are closely related in such a DMFS, their goal is to provide designers with algorithms that enable rapid simulation and control of these DMFS devices. In this paper, the effects of variations in the basic array-layout design, droplet-routing control algorithms, and droplet spacing on system performance are characterized. DMFS arrays with hardware limited row-column addressing are considered, and a polynomial-time algorithm for coordinating droplet movement under such hardware limitations is developed. To demonstrate the capabilities of our system, we describe example scenarios, including dilution control and minimalist layouts, in which our system can be successfully applied. Index Terms—Array layout, biochips, digital microfluidics, droplet routing, lab-on-a-chip, performance analysis, row–column addressing. I.

We present an architectural design and optimization methodology for performing biochemical reactions using two-dimensional electrowetting arrays. We define a set of basic microfluidic operations and leverage electronic design automation principles for system partitioning, resource allocation, and operation scheduling. Fluidic operations are carried out through the electrostatic configuration of a set of grid points. While concurrency is desirable to minimize processing time, the size of the two-dimensional array limits the number of concurrent operations of any type. Furthermore, functional dependencies between the operations also limit concurrency. We use integer linear programming to minimize the processing time by automatically extracting parallelism from a biochemical assay. As a case study, we apply our optimization method to the polymerase chain reaction, which is an important step in many labon -a-chip biochemical applications. Keywords: Architectural optimization, integer linear programming, microelectrofluidics, partition map, reconfigurable architecture, scheduling. 2 1

Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, deoxyribonucleic acid (DNA) sequencing, and other laboratory procedures involving molecular biology. In contrast to continuous-flow systems that rely on permanently etched microchannels, micropumps, and microvalves, digital microfluidics offers a scalable system architecture and dynamic reconfigurability; groups of unit cells in a microfluidics array can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. As more bioassays are executed concurrently on a biochip, system integration and design complexity are expected to increase dramatically. This paper presents an overview of an integrated system-level design methodology that attempts to address key issues in the synthesis, testing and reconfiguration of digital microfluidics-based biochips. Different actuation mechanisms for microfluidics-based biochips, and associated design-automation trends and challenges are also discussed. The proposed top-down design-automation approach is expected to relieve biochip users from the burden of manual optimization of bioassays, time-consuming hardware design, and costly testing and maintenance procedures, and it will facilitate the integration of fluidic components with a microelectronic component in next-generation systems-on-chips (SOCs).

Recent events have heightened the need for fast, accurate, and reliable biological/chemical sensor systems for critical locations. As droplet-based microelectrofluidic sensor systems become widespread in these safety-critical biomedical applications, reliability emerges as a critical performance parameter. In order to ensure the operational health of such safety-critical systems, they need to be monitored for defects, not only after manufacturing, but also during in-field operation. In this paper, we present a cost-effective concurrent test methodology for droplet-based microelectrofluidic systems. We present a classification of catastrophic and parametric faults in such systems and show how faults can be detected by electrostatically controlling and tracking droplet motion. We then present a fault simulation approach based on tolerance analysis using Monte-Carlo simulation to characterize the impact of parameter variations on system performance. Finally, we present experimental results on a droplet-based microelectrofluidic system for a real-time polymerase chain reaction application.

In this paper we present an approach to coordinate the motions of droplets in digital microfluidic systems, a new class of lab-on-a-chip systems for biochemical analysis. A digital microfluidic system typically consists of a planar array of cells with electrodes that control the droplets. The primary challenge in using droplet-based systems is that they require the simultaneous coordination of a potentially large number of droplets on the array as the droplets move, mix, and split. In this paper we describe a general-purpose system that uses simple algorithms and yet is versatile. First, we present a semi-automated approach to generate the array layout in terms of components. Next, we discuss simple algorithms to select destination components for the droplets and a decentralized scheme for components to route the droplets on the array. These are then combined into a reconfigurable system that has been simulated in software to perform analyses such as the DNA polymerase chain reaction. The algorithms have been able to successfully coordinate hundreds of droplets simultaneously and perform one or more chemical analyses in parallel. Because it is challenging to analytically characterize the behavior of such systems, simulation methods to detect potential system instability are proposed.

Abstract. Recent years have seen the emergence of droplet-based microfluidic systems for safety-critical biomedical applications. In order to ensure reliability, microsystems incorporating microfluidic components must be tested adequately. In this paper, we investigate test planning and test resource optimization for droplet-based microfluidic arrays. We first formulate the test planning problem and prove that it is NP-hard. We then describe an optimization method based on integer linear programming (ILP) that yields optimal solutions. Due to the NP-hard nature of the problem, we develop heuristic approaches for optimization. Experimental results indicate that for large array sizes, the heuristic methods yield solutions that are close to provable lower bounds. These heuristics ensure scalability and low computation cost.

Composite microsystems that incorporate microelectromechanical and microelectrofluidic devices are emerging as the next generation of system-on-a-chip (SOC). We present a performance comparison between two types of microelectrofluidic systems (MEFS): continuous-flow systems and droplet-based systems. The comparison is based on a specific microelectrofluidic application---a polymerase chain reaction (PCR) system. The behavioral modeling, simulation, and performance evaluation are based on a SystemC design environment. The performance comparison includes the system throughput, system-correction capacity, system-processing capacity, and system-design complexity. By using our system-performance evaluation environment, we demonstrated that the droplet-based MEFS provides higher performance, as well as lower design and integration complexity.

Microfluidics-based biochips, also referred to as lab-on-a-chip, are devices that integrate fluidhandling functions such as sample preparation, analysis, separation, and detection. This emerging technology combines electronics with biology to open new application areas such as point-of-care diagnosis, on-chip DNA analysis, and automated drug discovery. We propose a design automation method for pin-constrained biochips that manipulate nanoliter volumes of discrete droplets on a microfluidic array. In contrast to the direct-addressing scheme that has been studied thus far in the literature, we assign a small number of independent control pins to a large number of electrodes in the biochip, thereby reducing design complexity and product cost. The design procedure relies on a droplet-trace-based array partitioning scheme and an efficient pin assignment technique, referred to as the “Connect-5 algorithm. ” The proposed method is evaluated using a set of multiplexed bioassays.

Microfluidics-based biochips for biochemical analysis are currently receiving much attention. They automate highly repetitive laboratory procedures by replacing cumbersome equipment with miniaturized and integrated systems. As these microfluidics-based microsystems become more complex, manufacturing yield will have significant influence on production volume and product cost. We propose an interstitial redundancy approach to enhance the yield of biochips that are based on droplet-based digital microfluidics. In this design method, spare cells are placed in the interstitial sites within the microfluidic array, and they replace neighboring faulty cells via local reconfiguration. The proposed design method is evaluated using a set of concurrent real-life bioassays. The defect-tolerant design approach based on space redundancy and local reconfiguration is expected to facilitate yield enhancement of microfluidics-based biochips, especially for the emerging marketplace.

Thermal management has emerged as a critical issue in the design of integrated circuits (ICs). As feature sizes decrease and package densities increase, current package-level cooling techniques will soon become inadequate. While a number of MEMS-based cooling solutions have been proposed to address cooling at the IC level, many are not equipped to address the problem of real-time active and "smart" cooling, where hotter thermal regions (i.e., hot areas) are detected and subsequently cooled at an increased rate. We describe an alternative cooling method, on a platform we call "d igital microfluidics ," where nanoliter-sized discrete liquid droplets immersed in oil are manipulated. Cooling droplets are actuated independently in user-defined patterns over an array of electrodes by electrowetting, eliminating the need for external pumps. This paper presents the effects of temperature-dependent system parameters on droplet transport in this digital microfluidic platform. We demonstrate experimentally that under a fixed frequency, the minimum voltage required to oscillate a microliter-sized droplet across a linear electrode array decreases as much as 30% for a 50C temperature increase.