In droplet microfluidics, aqueous droplets are typically separated by an oil phase to ensure containment of molecules in individual droplets of nano-to-picoliter volume. An interesting variation of this method involves bringing two phospholipid-coated droplets into contact to form a lipid bilayer in-between the droplets. These interdroplet bilayers, created by manual pipetting of microliter droplets, have proved advantageous for the study of membrane transport phenomena, including ion channel electrophysiology.In this study, we adapted the droplet microfluidics methodology to achieve automated formation of interdroplet lipid bilayer arrays. We developed a 'millifluidic' chip for microliter droplet generation and droplet packing, which is cast from a 3D-printed mould. Droplets of 0.7-6.0 μL volume were packed as homogeneous or heterogeneous linear arrays of 2-9 droplets that were stable for at least six hours. The interdroplet bilayers had an area of up to 0.56 mm 2 , or an equivalent diameter of up to 850 μm, as determined from capacitance measurements. We observed osmotic water transfer over the bilayers as well as sequential bilayer lysis by the pore-forming toxin melittin. These millifluidic interdroplet bilayer arrays combine the ease of electrical and optical access of manually pipetted microdroplets with the automation and reproducibility of microfluidic technologies. Moreover, the 3D-printing based fabrication strategy enables the rapid implementation of alternative channel geometries, e.g. branched arrays, with a design-to-device time of just 24-48 hours.

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Very large scale computations are now becoming routinely used as a methodology to undertake scientific research. In this context, 'provenance systems' are regarded as the equivalent of the scientist's logbook for in silico experimentation: provenance captures the documentation of the process that led to some result. Using a protein compressibility analysis application, we derive a set of generic use cases for a provenance system. In order to support these, we address the following fundamental questions: what is provenance? how to record it? what is the performance impact for grid execution? what is the performance of reasoning? In doing so, we define a technologyindependent notion of provenance that captures interactions between components, internal component information and grouping of interactions, so as to allow us to analyse and reason about the execution of scientific processes. In order to support persistent provenance in heterogeneous applications, we introduce a separate provenance store, in which provenance documentation can be stored, archived and queried independently of the technology used to run the application. Through a series of practical tests, we evaluate the performance impact of such a provenance system. In summary, we demonstrate that provenance recording overhead of our prototype system remains under 10% of execution time, and we show that the recorded information successfully supports our use cases in a performant manner.

ABSTRACT:Molecular materials are endowed with unique properties of unrivaled potential for high density integration of computing systems. Present applications of molecules range from organic semiconductor materials for low-cost circuits to genetically modified proteins for commercial imaging equipment. To fully realize the potential of molecules in computation, information processing concepts that relinquish narrow prescriptive control over elementary structures and functions are needed, and self-organizing architectures have to be developed. Investigations into qualitatively new concepts of information processing are underway in the areas of reaction-diffusion computing, self-assembly computing, and conformation-based computing. Molecular computing is best considered not as competitor for conventional computing, but as an opportunity for new applications. Microrobotics and bioimmersive computing are among the domains likely to benefit from advances in molecular computing. Progress will depend on both novel computing concepts and innovations in materials. This article reviews current directions in the use of bulk and single molecules for information processing. KEY WORDS:polymer electronics, molecular switches, self-assembly computing, conformation-based computation, self-organizing materials, bioimmersive computing

The conformational dynamics of enzymes is a computational resource that fuses milieu signals in a nonlinear fashion. Response surface methodology can be used to elicit computational functionality from enzyme dynamics. We constructed a tabletop prototype to implement enzymatic signal processing in a device context and employed it in conjunction with malate dehydrogenase to perform the linearly inseparable exclusive-or operation. This shows that proteins can execute signal processing operations that are more complex than those performed by individual threshold elements. We view the experiments reported, though restricted to the two-variable case, as a stepping stone to computational networks that utilize the precise reproducibility of proteins, and the concomitant reproducibility of their nonlinear dynamics, to implement complex pattern transformations.

The quintessential living element of all organisms is the cell-a fluid-filled compartment enclosed, but not isolated, by a layer of amphiphilic molecules that self-assemble at its boundary. Cells of different composition can aggregate and communicate through the exchange of molecules across their boundaries. The astounding success of this architecture is readily apparent throughout the biological world. Inspired by the versatility of nature's architecture, we investigate aggregates of membrane-enclosed droplets as a design concept for robotics. This will require droplets capable of sensing, information processing, and actuation. It will also require the integration of functionally specialized droplets into an interconnected functional unit. Based on results from the literature and from our own laboratory, we argue the viability of this approach. Sensing and information processing in droplets have been the subject of several recent studies, on which we draw. Integrating droplets into coherently acting units and the aspect of controlled actuation for locomotion have received less attention. This article describes experiments that address both of these challenges. Using lipid-coated droplets of Belousov-Zhabotinsky reaction medium in oil, we show here that such droplets can be integrated and that chemically driven mechanical motion can be achieved.

a b s t r a c tMicrofluidics provides a powerful technology for both the production of molecular computing components and for the implementation of molecular computing architectures. The potential commercial applications of microfluidics drive rapid progress in this field-but at the same time focus interest on materials that are compatible with physiological aqueous conditions. For engineering applications that consider a broader range of physico-chemical conditions the narrow set of established materials for microfluidics can be a challenge. As a consequence of the large surface to volume ratio inherent in microfluidic technology the material of the device can greatly affect the chemistry in the channels of the device. In practice it is necessary to co-develop the chemical medium to be used in the device together with the microfluidic devices. We describe this process for a molecular computing architecture that makes use of excitable lipid-coated droplets of Belousov-Zhabotinsky reaction medium as its active processing components. We identify fluoropolymers with low melting temperature as a suitable substrate for microfluidics to be used in conjunction with Belousov-Zhabotinsky droplets in decane.

Robot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighboring robots. While current swarm implementations can be large in size (e.g., 1,000 robots), they are typically constrained to working in highly controlled indoor environments. Moreover, a common property of swarms is the underlying assumption that the robots act in close proximity of each other (e.g., 10 body lengths apart), and typically employ uninterrupted, situated, close-range communication for coordination. Many real world applications, including environmental monitoring and precision agriculture, however, require scalable groups of robots to act jointly over large distances (e.g., 1,000 body lengths), rendering the use of dense swarms impractical. Using a dense swarm for such applications would be invasive to the environment and unrealistic in terms of mission deployment, maintenance and post-mission recovery. To address this problem, we propose the sparse swarm concept, and illustrate its use in the context of four application scenarios. For one scenario, which requires a group of rovers to traverse, and monitor, a forest environment, we identify the challenges involved at all levels in developing a sparse swarm-from the hardware platform to communication-constrained coordination algorithms-and discuss potential solutions. We outline open questions of theoretical and practical nature, which we hope will bring the concept of sparse swarms to fruition.