Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer: Design, Synthesis, and Adaptation

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Abstract
Flow-based microfluidic biochips have emerged as a promising platform for biochemical experiments. These chips contain transportation channels and operational devices that are controlled by microvalves, which are actuated by external controllers. As the complexity of experiments conducted on these chips continues to increase, control multiplexers (MUXes) have become essential for actuating a large number of valves. However, current binary-coding-based MUXes do not fully utilize the coding capacity and suffer from reliability issues due to long total length of channels and high control channel density. In this article, we propose the combinatorial coding, a novel MUX coding strategy, along with an algorithm to synthesize combinatorial-coding-based MUXes (CoMUXes) of arbitrary sizes with the theoretical maximum coding capacity. We also develop a simplification method to reduce the number of valves and the total length of control channels in CoMUXes, thereby improving their reliability. Additionally, we develop a reliability-aware adaptation method to reliably integrate the CoMUXes into the main functional part of the designs. We compare CoMUX with state-of-the-art MUXes under different control demands with up to $10 \times 2^{13}$ independent control channels. Experimental results show that CoMUXes can reliably address more independent control channels with fewer resources. For instance, when the number of control channels to be controlled is up to $10 \times 2^{13}$ , compared to a state-of-the-art MUX, the optimized CoMUX reduces the number of required flow channels by 44% and the number of valves by 90%. The proposed adaptation method is also tested to be capable of significantly reducing area usage, total length of control channels, and the risk of having defects.
Funding Information
  • JC STEM Lab of Intelligent Design Automation funded by The Hong Kong Jockey Club Charities Trust
  • Research Grants Council of Hong Kong SAR (CUHK14217022)
  • Deutsche Forschungsgemeinschaft Forschungsgemeinschaft (456006534, 515003344)

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