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Abstract—Microfluidic-based biochips are replacing the con-ventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets on an array of electrodes. Microfluidic operations, such as transport, mixing, split, are performed on this array by routing the corresponding droplets on a series of electrodes. Several approaches have been proposed for the compilation of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling, placement and routing of the operations in the application. To simplify the compilation problem, researchers have assumed an abstract droplet size of one electrode. However, the droplet size abstraction is not realistic and it impacts negatively the execution of the biochemical application, leading in most cases to its failure. Hence the existing compilation approaches have to be revisited to consider the size of the droplets. In this paper we take the first step towards a droplet size-aware compilation by proposing a routing algorithm that considers the droplet size. Our routing algorithm is developed for a novel digital microfluidic biochip architecture based on Active Matrix Electrowetting on Dielectric, which uses a thin film transistor array for the electrodes. We also implement a simulator that allows us to perform the needed adaptations and to validate the proposed routing algorithm. I

Synthesis of biochemical applications on digital microfluidic biochips with operation variability

Abstract—Microfluidic-based biochips are replacing the con-ventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets. Researchers have presented approaches for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling and place-ment of the operations in the application. Existing approaches consider that on-chip operations, such as splitting a droplet of liquid, are perfect. However, these operations have variability margins, which can impact the correctness of the biochemical application. We consider that a split operation, which goes beyond specified variability bounds, is faulty. The fault is detected using on-chip volume sensors. We have proposed an abstract model for a biochemical application, consisting of a sequencing graph, which can capture all the fault scenarios in the application. Starting from this model, we have proposed a synthesis approach that, for a given chip area and number of sensors, can derive a fault-tolerant implementation. Two fault-tolerant scheduling techniques have been proposed and compared. We show that, by taking into account fault-occurrence information, we can derive better quality implementations, which leads to shorter application completion times, even in the case of faults. The proposed synthesis approach under operation variability has been evaluated using several benchmarks. I

Mobile Microfluidics

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

OpenDrop: An Integrated Do-It-Yourself Platform for Personal Use of Biochips

Biochips, or digital labs-on-chip, are developed with the purpose of being used by laboratory technicians or biologists in laboratories or clinics. In this article, we expand this vision with the goal of enabling everyone, regardless of their expertise, to use biochips for their own personal purposes. We developed OpenDrop, an integrated electromicrofluidic platform that allows users to develop and program their own bio-applications. We address the main challenges that users may encounter: accessibility, bio-protocol design and interaction with microfluidics. OpenDrop consists of a do-it-yourself biochip, an automated software tool with visual interface and a detailed technique for at-home operations of microfluidics. We report on two years of use of OpenDrop, released as an open-source platform. Our platform attracted a highly diverse user base with participants originating from maker communities, academia and industry. Our findings show that 47% of attempts to replicate OpenDrop were successful, the main challenge remaining the assembly of the device. In terms of usability, the users managed to operate their platforms at home and are working on designing their own bio-applications. Our work provides a step towards a future in which everyone will be able to create microfluidic devices for their personal applications, thereby democratizing parts of health care