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Microfluidics is a flourishing field, enabling a wide range of biochemical and clinical applications such as cancer screening, micro-physiological system engineering, high-throughput drug testing, and point-of-care diagnostics. However, fabrication of microfluidic devices is often complicated, time consuming, and requires expensive equipment and sophisticated cleanroom facilities. Three-dimensional (3D) printing presents a promising alternative to traditional techniques such as lithography and PDMS-glass bonding, not only by enabling rapid design iterations in the development stage, but also by reducing the costs associated with institutional infrastructure, equipment installation, maintenance, and physical space. With the recent advancements in 3D printing technologies, highly complex microfluidic devices can be fabricated via single-step, rapid, and cost-effective protocols, making microfluidics more accessible to users. In this review, we discuss a broad range of approaches for the application of 3D printing technology to fabrication of micro-scale lab-on-a-chip devices.

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We provide a less conservative (compared with our previous results) lower bound on the horizon length for a stabilizing model predictive control algorithm where the terminal cost is not assumed to be a local control Lyapunov function. Our main additional assumption is that the value function is bounded by a linear function of a measure of the state uniformly in the horizon length.

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