Rapid advances in microfluidics technologies have facilitated the emergence of highly integrated lab-on-a-chip (LoC) biochip systems. With such a coin-sized biochip, complicated bioassay procedures can be executed efficiently without any human intervention. To ensure the correctness of assay outcomes, however, cross-contamination among different fluid samples and reagents needs to be dealt with separately during assay execution. As a consequence, washing operations have to be introduced and a washing path network needs to be established on the chip to remove the residues left behind in flow channels/devices. Also, chip drying after washing operations is crucial for maintaining some properties (e.g., pH values) of the subsequent reagents, so that precision degradation caused by residual buffer fluids can be avoided for those concentration-sensitive assays. To realize optimized assay procedures, we consider both washing operations and chip drying for the first time and propose an integer linear programming (ILP)-based path-driven washing and drying cooptimization method called PathDriver-WD for continuous-flow LoC biochip systems. The proposed method includes the following four key techniques: 1) The necessity of contamination removals and channel drying is analyzed systemically to avoid unnecessary washing and drying operations, 2) washing and drying operations are integrated with the regular removal of excess fluids, so that extra channel occupation can be minimized, 3) practical computation models are adopted to evaluate the durations of different washing and drying operations, and 4) optimized washing/drying paths and time windows are computed and assigned so that the completion time of assays can be minimized. Simulation results on multiple benchmarks demonstrate that the proposed method leads to highly efficient washing and drying procedures as well as minimized assay completion time.

Flow-based microfluidic biochips have attracted much attention over the past two decades. By integrating diverse micro-components, e.g., mixers and filters, on a miniaturized planar substrate, complicated bioassays such as protein crystallization and drug screening can be executed automatically without requiring human invention, thus becoming a promising alternative to traditional cumbersome laboratory equipment. As manufacturing technology advances, it has become possible to implement hundreds of thousands of microvalves within a single chip. This breakthrough has given rise to fully programmable valve array (FPVA) biochips, representing a next-generation platform in flow-based microfluidics that offers enhanced reconfigurability and operational flexibility. Nevertheless, the exponential increase in valve density has introduced significant design complexity when implementing sophisticated assay protocols. As a result, the design automation of FPVAs has emerged as a critical research frontier, attracting considerable attention from both academia and industry. This review article systematically examines recent advances in FPVA design automation, involving computer-aided design methods for architectural synthesis, volume management, sample preparation, automated testing, fault localization, error recovery, and washing optimization. These techniques enable FPVA users to concentrate on assay protocol development while delegating implementation-specific design and optimization tasks to design automation tools. Furthermore, we analyze emerging security implications in FPVAs, particularly focusing on bioassay accuracy and reliability that ensure experimental reproducibility. Finally, potential trajectories for future research are discussed in detail to further promote the integration level and widespread application of FPVAs.

Advanced digital microfluidic biochips based on technologies such as micro-electrode-dot-array (MEDA) and active matrix (AM) provide enhanced functionality compared to conventional biochips. Owing to the larger ratio of droplet size to electrode size, these platforms allow finer control of droplets and diagonal movement. Additionally, they allow dynamic grouping of micro-electrodes to form subsystems that can perform fluidic operations. Shape morphing is a key feature of MEDA/AM biochips that results in faster fluidic operations, thereby improving the efficiency of bioassays. To establish the benefits of shape morphing, we first numerically simulate the shape morphing operation. We employ a simplified 2-D flow model incorporating interface tracking through a level-set method to numerically simulate shape morphing induced by micro-electrode actuation. We also validate our numerical results with COMSOL simulations and experiments performed on MEDA/AM biochips. The validated shape morphing operations are subsequently used to optimize droplet routing for benchmark bioassays. We propose an algorithm to significantly reduce the size of the routing problem and the time needed to solve it. With the help of this improved approach, we show that droplet morphing operations reduce the time needed to complete bioassays.

Implantable neuroprostheses require stimulators with high channel counts and mechanical flexibility. Organic thin-film transistor (OTFT), an essential building block for flexible circuits and system, is a promising candidate. However, the development of photolithographic OTFTs for complete bioelectronic system integration remains a challenge, due to their limited yield and uniformity. This paper reports a 4-mask photolithographic OTFT circuit integration technology, which shows a high device yield of 100% (50/50) and small device variation in threshold voltage of 0.64 V and in mobility of 4.9%. Using a device-circuit-system co-design approach, we demonstrate an active-matrix neurostimulation array comprised of 1024 pixels of a 4T1C stimulation circuits, in which independent stimulation intensity levels can be programmed and current stimulus at all channels can output simultaneously. The electrical function of the complete neurostimulation system is verified, showing a small variation of 15.59% for the output stimulation currents among pixels. This OTFT-based neurostimulation system provides a potential solution for the next-generation neurostimulators with high channel counts and mechanical flexibility.