https://escholarship.org/content/qt3jh0x2hh/qt3jh0x2hh.pdf?t=odzwlj

Recent developments in microfluidic large scale integration.

Continuous-flow microfluidics rapidly evolved in the last decades as a solution to automate laboratory procedures in molecular biology and biochemistry. Therefore, the physical design of the corresponding chips, i.e., the placement and routing of the involved components and channels, received significant attention. Recently, several physical design solutions for this task have been presented. However, they often rely on general heuristics which traverse the search space in a rather arbitrary fashion and, additionally, consider placement and routing independently from each other. Consequently, the obtained results are often far from being optimal. In this work, a methodology is proposed which aims for determining close-to-optimal physical designs for continuous-flow microfluidic biochips. To this end, we consider all — or, at least, as much as possible — of the valid solutions. As this obviously yields a significant complexity, solving engines are utilized to efficiently traverse the search space and pruning schemes are proposed to reduce the search space without discarding too many promising solutions. Evaluations show that the proposed methodology is capable of determining optimal results for small experiments to be realized. For larger experiments, close-to-optimal results can efficiently be derived. Moreover, compared to the current state-of-the-art, improvements of up to 1–2 orders of magnitude can be observed.

Close-to-optimal placement and routing for continuous-flow microfluidic biochips

Continuous-flow microfluidic large-scale integration (mLSI) shows increasing importance in biological/chemical fields, thanks to its advantages in miniaturization and high throughput. Current mLSI is designed manually, which is time-consuming and error-prone. In recent years, design automation research for mLSI has evolved rapidly, aiming to replace manual labor by computers. However, previous design automation approaches used to design each microfluidic layer separately and over-simplify the layer interactions to various degrees, which resulted in a gap between realistic requirements and automatically generated designs. In this paper, we propose a module model library to accurately model microfluidic components involving layer interactions; and we propose a co-layout synthesis tool, Columba, which generates AutoCAD-compatible designs that fulfill all designs rules and can be directly used for mask fabrication. Columba takes plain-text netlist descriptions as inputs, and performs simultaneous placement and routing for multiple layers while ensuring the planarity of each layer. We validate Columba by fabricating two of its output designs. Columba is the first design automation tool that can seamlessly synchronize with the manufacturing flow.

Columba 2.0: A Co-Layout Synthesis Tool for Continuous-Flow Microfluidic Biochips

In flow-based microfluidic biochips, microvalves on the control layer need to be connected to control pins via control channels. In application-specific and portable microfluidic devices, critical microvalves need to switch at the same time for correct functionality. Those microvalves are required to have equal or similar channel lengths to the control pin, so that the control signal can reach them simultaneously. This paper presents a practical control-layer routing flow (PACOR) considering the critical length-matching constraint. Major features of PACOR include: (1) effective candidate Steiner tree construction and selection methods for multiple microvalves based on the deferred-merge embedding (DME) algorithm and maximum weight clique problem (MWCP) formulation, (2) minimum cost flow-based formulation for simultaneous escape routing for improved routability, and (3) minimum-length bounded routing method to detour paths for length matching. Computational simulation results show effectiveness and efficiency of PACOR with promising matching results and 100% routing completion rate.

PACOR: practical control-layer routing flow with length-matching constraint for flow-based microfluidic biochips

Digital microfluidic biochips (DMFBs) integrated with processors and arrays of sensors form cyberphysical systems and consequently face a variety of unique, recently described security threats. It has been noted that techniques used for error recovery can provide some assurance of integrity when a cyberphysical DMFB is under attack. This paper proposes the use of such hardware for security purposes through the randomization of checkpoints in both space and time, and provides design guidelines for designers of such systems. We define security metrics and present techniques for improving performance through static checkpoint maps, and describe performance tradeoffs associated with static and random checkpoints. We also provide detailed classification of attack models and demonstrate the feasibility of our techniques with case studies on assays implemented in typical DMFB hardware.

Secure Randomized Checkpointing for Digital Microfluidic Biochips

Recent advances in flow-based microfluidic biochips have enabled the emergence of lab-on-a-chip devices for bimolecular recognition and point-of-care disease diagnostics. However, the adoption of flow-based biochips is hampered today by the lack of computer-aided design tools. Manual design procedures not only delay product development but they also inhibit the exploitation of the design complexity that is possible with current fabrication techniques. In this paper, we present the first practical problem formulation for automated control-layer design in flow-based microfluidic very large-scale integration (mVLSI) biochips and propose a systematic approach for solving this problem. Our goal is to find an efficient routing solution for control-layer design with a minimum number of control pins. The pressure-propagation delay, an intrinsic physical phenomenon in mVLSI biochips, is minimized in order to reduce the response time for valves, decrease the pattern set-up time, and synchronize valve actuation. Two fabricated flow-based devices and six synthetic benchmarks are used to evaluate the proposed optimization method. Compared with manual control-layer design and a baseline approach, the proposed approach leads to fewer control pins, better timing behavior, and shorter channel length in the control layer.

Control-Layer Routing and Control-Pin Minimization for Flow-Based Microfluidic Biochips

Sample preparation, which is a front-end process to produce droplets of the desired target concentrations from input reagents, plays a pivotal role in every assay, laboratory, and application in biomedical engineering and life science. The consumption of sample/buffer/waste is usually used to evaluate the effectiveness of a sample preparation process. In this paper, for the first time, we present an optimal sample preparation algorithm based on a minimum-cost maximum-flow model. By using the proposed model, we can obtain both the optimal cost of sample and buffer usage and the waste amount even for multiple-target concentrations. Experiments demonstrate that we can consistently achieve much better results not only in the consumption of sample and buffer but also the waste amount when compared with all the state-of-the-art of the previous approaches.

A network-flow-based optimal sample preparation algorithm for digital microfluidic biochips

A Network-Flow-Based Optimal Sample Preparation Algorithm for Digital Microfluidic Biochips

Recent advantages in flow-based microfluidic biochips have enabled the emergence of lab-on-a-chip devices for bimolecular recognition and point-of-care disease diagnostics. However, the adoption of flow-based biochips is hampered today by the lack of computer-aided design tools. Manual design procedures not only delay product development but they also inhibit the exploitation of the design complexity that is possible with current fabrication techniques. In this paper, we present the first practical problem formulation for automated control-layer design in flow-based microfluidic VLSI (mVLSI) biochips and propose a systematic approach for solving this problem. Our goal is to find an efficient routing solution for control-layer design with a minimum number of control pins. The pressure-propagation delay, an intrinsic physical phenomenon in mVLSI biochips, is minimized in order to reduce the response time for valves, decrease the pattern set-up time, and synchronize valve actuation. Two fabricated flow-based devices and five synthetic benchmarks are used to evaluate the proposed optimization method. Compared with manual control-layer design and a baseline approach, the proposed approach leads to fewer control pins, better timing behavior, and shorter channel length in the control layer.

Control-layer optimization for flow-based mVLSI microfluidic biochips

A digital micro fluidic biochip (DMFB) is an attractive platform for immunoassays, point-of-care clinical diagnostics, DNA sequencing, and other laboratory procedures in biochemistry. Effective testing methods are required to ensure robust DMFB operation and high confidence in the outcome of biochemical experiments. Prior work on DMFB testing does not address the problem of designing the test to minimize reliability degradation during test application. It also ignores physical constraints arising from fluidic behavior and the physics of electro wetting-on-dielectric. We develop a practical and realistic testing method by first systematically analyzing the influence of actuation voltage and actuation frequency on the distribution of the electric field, and its resulting effect on dielectric degradation. Next, we use this analysis to choose appropriate parameter settings for testing, and proposes a new pipelined scan-like testing method. Both static and dynamic fluidic constraints are considered in the new testing method, and a diagnosis technique is presented to easily locate defects. Finally, simulation results are presented to demonstrate the effectiveness of the proposed testing approach in minimizing test-completion time.

Trung Anh Dinh

Papers

Control-Layer Routing and Control-Pin Minimization for Flow-Based Microfluidic Biochips

A network-flow-based optimal sample preparation algorithm for digital microfluidic biochips

A Network-Flow-Based Optimal Sample Preparation Algorithm for Digital Microfluidic Biochips

Control-layer optimization for flow-based mVLSI microfluidic biochips

Reliability-Driven Pipelined Scan-Like Testing of Digital Microfluidic Biochips