Mengchu Li

mCFMB are rapidly advancing platforms for delicate bio-applications. The high complexity of biochip structures and application protocols drives the growing demand for design automation solutions. Current research enables the automatic synthesis of the physical layout and the scheduling and binding protocols of biochips, showcasing the significant potential of microfluidic design automation for improved resource utilization and reduced bioassay completion time. However, state-of-the-art synthesis methods primarily focus on device and operation levels, assuming flow paths are always available and neglecting interactions of flow and control channels. This creates a critical gap in the synthesis process, causing performance degradation, resource redundancy, or even infeasible designs. This work bridges this gap with a two-stage approach. First, we perform a mathematical model to synthesize a high-level protocol that specifies the paths and execution orders of fluid transportation operations. Specifically, we construct flow paths based on the fluidic architecture of a given biochip design and optimize scheduling schemes to minimize the completion time of a given bioassay. Next, we perform a simulation-based synthesis of control channel pressurization sequences to realize the high-level protocol. Experimental results confirm that the proposed approach efficiently validates flow paths for feasible designs, identifies conflicting design features in infeasible designs, and improves the design efficiency and quality: compared to the original designs, it reduces the average number of control channels by 49%, and compared to the preliminary work, it reduces the average fluid transportation time by 19% and the average program run time by 38%.

Multilayered continuous-flow microfluidic biochips are highly valued for their miniaturization and high bio-application throughput. However, challenges arise as the dynamic connections of channels, adjusted to satisfy varying demands of fluid transportation at different moments, complicate the execution of bioassays. The existing methods often focus on device binding and operation scheduling during high-level synthesis but overlook the topological connections within the microfluidic network. This oversight leads to mismanagement of conflicts between fluid transportations and erroneous assumptions about constant flow velocities, resulting in decreased accuracy and efficiency or even infeasibility of bioassay execution. To address this problem, we mathematically model the flow velocity that varies according to the dynamic changes of the topological connections between the on-chip components during the execution of the bioassay. Further integrating the flow velocity model into the high-level synthesis, we propose a quadratic programming (QP) method that constructs flow paths and optimizes scheduling schemes to minimize the bioassay completion time. Experimental results confirm that, compared with the state-of-the-art approach, our method shortened the bioassay completion time by an average of 40.9%.

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.

Inkjet-printed electronics has attracted considerable attention for low-cost mass production. High-density inkjet-printed designs can benefit from printing and drying in batches to avoid defects due to undesired ink redistribution and ink merging. The state-of-the-art approach decomposes the design into small objects, assigns the objects to different layers to be printed in different iterations, and minimizes the number of layers to reduce the number of iterations. However, it overlooks the differences in the printing and drying time between different layers and thus cannot properly model the impact of different layer assignment solutions on the manufacturing cycle time. In this work, we propose a row-based printing model that simulates the inkjet-printing mechanism and an integral Gaussian drying model that evaluates the local evaporation rate to approximate the printing and drying process of inkjet-printed manufacturing. Based on these models, we propose a mixed-integer-linear programming (MILP) method called the manufacturing model to minimize the manufacturing cycle time and avoid defects by optimally assigning objects to different iterations to be printed and dried in batches. Experimental results confirm that, compared with the preliminary work, manufacturing using our optimized solutions required up to 42.7% less time.

Control channels on microfluidic large-scale integration (mLSI) chips are prone to blockage and leakage defects. In this work, we propose a built-in self-test (BIST) method that drastically improves the test efficiency. Given n to-be-tested control channels, we reduced the number of test patterns for blockage and leakage tests from [EQUATION] to 1, and from ⌈log₂(n + 1)⌉ to ⌈log₂(χ^{(G) + 1)}⌉, respectively, where χ(G) denotes the vertex chromatic number of a graph G consisting of n vertices. We fabricated our design and demonstrated the feasibility and efficiency of our method.

After decades of development, flow-based microfluidic biochips have become an increasingly attractive platform for biochemical experiments. The fluid transportation and the on-chip device operation are controlled by microvalves, which are driven by external pneumatic controllers. To meet the increasingly complex experimental demands, the number of microvalves has significantly increased, making it necessary to adopt multiplexers (MUXes) for the actuation of microvalves. However, existing MUX designs have limited coding capacities, resulting in area overhead and excessive chip-to-world interface. This paper proposes a novel gate structure for modifying the current MUX architecture, along with a mixed coding strategy that achieves the maximum coding capacity within the modified MUX architecture. Additionally, an efficient synthesis tool for the mixed-coding-based MUXes (LaMUXes) is presented. Experimental results demonstrate that the LaMUX is exceptionally efficient, substantially reducing the usage of pneumatic controllers and microvalves compared to existing MUX designs.