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Biosample analysis often requires the purification, separation, or fractionation of a biofluid prior to transport to the biosensor. Deterministic lateral displacement (DLD) is a size-based microfluidic separation technique that shows promise for biosample preparation. Recently, high-throughput DLD separation has been demonstrated with airfoil-shaped pillars at higher flow rates, but this also changes separation dynamics as the Reynolds number (Re) increases. In this work, the particle trajectories in the airfoil DLD with two different angle-of-attacks (AoAs) were studied at a range of Re with alterations of fluid viscosity to mimic biological fluids. Previous studies have found that the critical diameter (Dc) decreases as Re climes. We demonstrated that variations of the fluid viscosity do not alter the separation dynamics if the Re is kept constant. As the associated Re of the flow increases, the Dc decreases regardless of viscosity. The negative AoA with an airfoil DLD pillar design provided the stronger Dc shift to negate pressure increases. 

Deterministic lateral displacement (DLD) is a microfluidic method for the continuous separation of particles based on their size. There is growing interest in using DLD for harvesting circulating tumor cells from blood for further assays due to its low cost and robustness. While DLD is a powerful tool and development of high-throughput DLD separation devices holds great promise in cancer diagnostics and therapeutics, much of the experimental data analysis in DLD research still relies on error-prone and time-consuming manual processes. There is a strong need to automate data analysis in microfluidic devices to reduce human errors and the manual processing time. In this work, a reliable particle detection method is developed as the basis for the DLD separation analysis. Python and its available packages are used for machine vision techniques, along with existing identification methods and machine learning models. Three machine learning techniques are implemented and compared in the determination of the DLD separation mode. The program provides a significant reduction in video analysis time in DLD separation, achieving an overall particle detection accuracy of 97.86% with an average computation time of 25.274 s. 

Abstract As technology becomes increasingly miniaturized, thermal management becomes challenging to keep devices away from overheating due to extremely localized heat dissipation. Two-phase cooling or flow boiling in microspaces utilizes the highly efficient thermal energy transport of phase change from liquid to vapor. However, the excessive consumption of liquid-phase by highly localized heat source causes the two-phase flow maldistribution, leading to a significantly reduced heat transfer coefficient, high-pressure loss, and limited flow rate. In this study, flow boiling in a two-dimensional (2D) microgap heat sink with a hydrophilic coating is investigated with bubble morphology, heat transfer, and pressure drop for conventional (nonhydrophilic) and hydrophilic heat sinks. The experiments are carried out on a stainless steel (SS) plate, having a microgap depth of 170 μm using de-ionized (DI) water at room temperature. Two different hydrophilic surfaces (partial and full channel shape) are fabricated on the heated surface to compare the thermal performance with the conventional surface. Vapor films and slugs are flushed quickly on the hydrophilic surfaces, resulting in heat transfer enhancement on the hydrophilic heat sink compared to the conventional heat sink. The channel hydrophilic heat sink shows better cooling performance and pressure stability as it provides a smooth route for the incoming water to cool the hot spot. Moreover, the artificial neural network (ANN) prediction of heat transfer coefficient shows a good agreement with the experimental results as data fit within ±5% average error. 

A recent development in portable biosensors allows rapid, accurate, and on-site detection of biomarkers, which helps to prevent disease spread by the control of sources. Less invasive sample collection is necessary to use portable biosensors in remote environments for accurate on-site diagnostics and testing. For non- or minimally invasive sampling, easily accessible body fluids, such as saliva, sweat, blood, or urine, have been utilized. It is also imperative to find accurate biomarkers to provide better clinical intervention and treatment at the onset of disease. At the same time, these reliable biomarkers can be utilized to monitor the progress of the disease. In this review, we summarize the most recent development of portable biosensors to detect various biomarkers accurately. In addition, we discuss ongoing issues and limitations of the existing systems and methods. Lastly, we present the key requirements of portable biosensors and discuss ideas for functional enhancements. 

Recent advances in nanomaterial preparation and printing technologies provide unique opportunities to develop flexible hybrid electronics (FHE) for various healthcare applications. Unlike the costly, multi-step, and error-prone cleanroom-based nano-microfabrication, the printing of nanomaterials offers advantages, including cost-effectiveness, high-throughput, reliability, and scalability. Here, this review summarizes the most up-to-date nanomaterials, methods of nanomaterial printing, and system integrations to fabricate advanced FHE in wearable and implantable applications. Detailed strategies to enhance the resolution, uniformity, flexibility, and durability of nanomaterial printing are summarized. We discuss the sensitivity, functionality, and performance of recently reported printed electronics with application areas in wearable sensors, prosthetics, and health monitoring implantable systems. Collectively, the main contribution of this paper is in the summary of the essential requirements of material properties, mechanisms for printed sensors, and electronics. 

Abstract The development of wireless implantable sensors and integrated systems, enabled by advances in flexible and stretchable electronics technologies, is emerging to advance human health monitoring, diagnosis, and treatment. Progress in material and fabrication strategies allows for implantable electronics for unobtrusive monitoring via seamlessly interfacing with tissues and wirelessly communicating. Combining new nanomaterials and customizable printing processes offers unique possibilities for high‐performance implantable electronics. Here, this report summarizes the recent progress and advances in nanomaterials and printing technologies to develop wireless implantable sensors and electronics. Advances in materials and printing processes are reviewed with a focus on challenges in implantable applications. Demonstrations of wireless implantable electronics and advantages based on these technologies are discussed. Lastly, existing challenges and future directions of nanomaterials and printing are described.