Pressure sensors integrated in surfaces, such as the floor, can enable movement, event, and object detection with relatively little effort and without raising privacy concerns, such as video surveillance. Usually, this requires a distributed array of sensor pixels, whose design must be optimized according to the expected use case to reduce implementation costs while providing sufficient sensitivity. In this work, we present an unobtrusive smart floor concept based on floor tiles equipped with a printed piezoelectric sensor matrix. The sensor element adds less than 130 µm in thickness to the floor tile and offers a pressure sensitivity of 36 pC/N for a 1 cm2 pixel size. A floor model was established to simulate how the localized pressure excitation acting on the floor spreads into the sensor layer, where the error is only 1.5%. The model is valuable for optimizing the pixel density and arrangement for event and object detection while considering the smart floor implementation in buildings. Finally, a demonstration, including wireless connection to the computer, is presented, showing the viability of the tile to detect finger touch or movement of a metallic rod.
Roll-to-roll UV nanoimprinting is a powerful method for the mass fabrication of nano-and microstructured surfaces, which are highly interesting for many technological applications (e.g., in the fields of optics, electronics, biomimetic, and microfluidics). When setting up a production process based on this technique, one of the main challenges is the prevention of defects (mainly entrapped air during filling and fractures during demolding). This can be cost-and time-intensive as it is mainly done by trial and error. An improved theoretical understanding of defect generation and its prediction for certain material and process parameters is therefore desirable. To accomplish this, we developed COMSOLbased two-dimensional (2D) and three-dimensional (3D) computer simulations for the two key stages of UV nanoimprinting (filling and demolding) and validated them by corresponding roll-to-roll as well as step-and-repeat experiments. Regarding filling, the investigated parameters are template and substrate contact angles; resin viscosity, velocity, and thickness during filling; as well as feature geometry. In summary, it is beneficial for filling to have low template contact angles; high substrate contact angles; low resin viscosity and velocity; as well as inclined sidewalls, low-aspect-ratio features, and a sufficient resin thickness (whereby lack of one of these factors can be compensated by others). Interestingly, nanoscale features are much easier to fill than microscale features in practice (which is not due to reduced bubble trapping but due to enhanced gas dissolution). Regarding demolding, we studied the sidewall angle, fillet radius, size, and elastic modulus of the features. In addition, we compared demolding by roll-to-roll and by stepand-repeat considering the radius of rotation and we decoupled bending, adhesion, and friction to investigate their relative contributions. We could demonstrate quantitatively that for demolding, it is advantageous to have small features, inclined sidewalls, rounded corners, and a large radius of rotation. The dominant effect for nanostructures is adhesion, whereas for microstructures, it is friction. Moreover, demolding by tilting (step-and-repeat) exerts less stress on the imprint than demolding using a roll-to-roll approach. Finally, we present a 3D demolding simulation that identifies the most vulnerable positions of a geometry. From the lessons learned from our filling and demolding simulations, we could demonstrate the defect-free roll-to-roll UV nanoimprinting of a challenging pattern (cuboids with vertical sidewalls).
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