Droplet-based "digital" microfluidics technology has now come of age and software-controlled biochips for healthcare applications are starting to emerge. However, today's digital microfluidic biochips suffer from the drawback that there is no feedback to the control software from the underlying hardware platform. Due to the lack of precision inherent in biochemical experiments, errors are likely during droplet manipulation, but error recovery based on the repetition of experiments leads to wastage of expensive reagents and hard-to-prepare samples. By exploiting recent advances in the integration of optical detectors (sensors) in a digital microfluidics biochip, we present a "physicalaware" system reconfiguration technique that uses sensor data at intermediate checkpoints to dynamically reconfigure the biochip. A cyberphysical re-synthesis technique is used to recompute electrode-actuation sequences, thereby deriving new schedules, module placement, and droplet routing pathways, with minimum impact on the time-to-response.
In liquid composite molding, such as RTM or SRIM, the dry reinforcement is first compressed in the mold, and then the resin is injected into the mold cavity and cured. Knowledge of the compressibility of the reinforcement is important in order to estimate the mold closing force and the attainable range of fiber volume fraction. Moreover, in a lay‐up composed of several types of fabrics, the compressibility of each fabric should be known to predict the thickness of each fabric layer, which is a prerequisite for the mold filling simulation. In this work, the relaxation and compressibility of a new sandwich fabric, Multimat®, and its components (a weft knit and a random mat) were studied and compared with a woven fabric. The different fabric relaxation behavior is explained in terms of fabric stiffness and volumetric dissipation energy. Fabric compression tests were performed by taking the fabric relaxation behavior into account. Fabric compression curves are fitted with the power law equation and agree well with the clamping pressure experimentally measured with a pressure transducer in an RTM mold. The influence of the number of layers was also investigated. Finally the compressibility of the Multimat is correlated to its components with a simple model.
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