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Abstract Microfluidic valves play a key role within microfluidic systems by regulating fluid flow through distinct microchannels, enabling many advanced applications in medical diagnostics, lab‐on‐chips, and laboratory automation. While microfluidic systems are often limited to planar structures, 3D printing enables new capabilities to generate complex designs for fluidic circuits with higher densities and integrated components. However, the control of fluids within 3D structures presents several difficulties, making it challenging to scale effectively and many fluidic devices are still often restricted to quasi‐planar structures. Incorporating mechanical metamaterials that exhibit spatially adjustable mechanical properties into microfluidic systems provides an opportunity to address these challenges. Here, systematic computational and experimental characterization of a modified re‐entrant honeycomb structure are performed to generate a modular metamaterial for an active device that allows us to directly regulate flow through integrated, multiplexed fluidic channels “one‐at‐a‐time,” in a manner that is highly scalable. A design algorithm is presented, so that this architecture can be extended to arbitrary geometries, and it is expected that by incorporation of mechanical metamaterial designs into 3D printed fluidic systems, which themselves are readily expandable to any complex geometries, will enable new biotechnological and biomedical applications of 3D printed devices.
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A compiler for cyber-physical digital microfluidic biochips
Programmable microfluidic laboratories-on-a-chip (LoCs) offer the benefits of automation and miniaturization to the life sciences. This paper presents an updated version of the BioCoder language and a fully static (offline) compiler that can target an emerging class of LoCs called Digital Microfluidic Biochips (DMFBs), which manipulate discrete droplets of liquid on a 2D electrode grid. The BioCoder language and runtime execution engine leverage advances in sensor integration to enable specification, compilation, and execution of assays (bio-chemical procedures) that feature online decision-making based on sensory data acquired during assay execution. The compiler features a novel hybrid intermediate representation (IR) that interleaves fluidic operations with computations performed on sensor data. The IR extends the traditional notions of liveness and interference to fluidic variables and operations, as needed to target the DMFB, which itself can be viewed as a spatially reconfigurable array. The code generator converts the IR into the following: (1) a set of electrode activation sequences for each basic block in the control flow graph (CFG); (2) a set of computations performed on sensor data, which dynamically determine the result of each control flow operation; and (3) a set of electrode activation sequences for each control flow transfer operation (CFG edge). The compiler is validated using a software simulator which produces animated videos of realistic bioassay execution on a DMFB.
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- PAR ID:
- 10067821
- Date Published:
- Journal Name:
- Proceedings of the 2018 International Symposium on Code Generation and Optimization - CGO 2018
- Page Range / eLocation ID:
- 365 to 377
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3168826
