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Cutting soft materials on the microscale has emerging applications in single-cell studies, tissue microdissection for organoid culture, drug screens, and other analyses. However, the cutting process is complex and remains incompletely understood. Furthermore, precise control over blade geometries, such as the blade tip radius, has been difficult to achieve. In this work, we use the Nanoscribe 3D printer to precisely fabricate micro-blades (i.e., blades <1 mm in length) and blade grid geometries. This fabrication method enables a systematic study of the effect of blade geometry on the indentation cutting of paraffin wax, a common tissue-embedding material. First, we print straight micro-blades with tip radius ranging from ~100 nm to 10 um. The micro-blades are mounted in a custom nanoindentation setup to measure the cutting energy during indentation cutting of paraffin. Cutting energy, measured as the difference in dissipated energy between the first and second loading cycles, decreases as blade tip radius decreases, until ~357 nm when the cutting energy plateaus despite further decrease in tip radius. Second, we expand our method to blades printed in unconventional configurations, including parallel blade structures and blades arranged in a square grid. Under the conditions tested, the cutting energy scales approximately linearly with the total length of the blades comprising the blade structure. The experimental platform described can be extended to investigate other blade geometries and guide the design of microscale cutting of soft materials., Comment: 15 pages, 3 figures, 7 supplementary figures

Droplet microfluidics, in which micro-droplets serve as individual reactors, has enabled a wide range of high-throughput biochemical processes. Unlike solid wells typically used in current biochemical assays, droplets are subject to instability and can undergo breakup, especially under fast flow conditions. Although the physics of single drops has been studied extensively, the flow of crowded drops or concentrated emulsions, where droplet volume fraction exceeds 80 percent, is relatively unexplored in microfluidics. In this article and the related invited lecture from the 74th Annual Meeting of the American Physical Society's Division of Fluid Dynamics, we describe the collective behavior of drops in a concentrated emulsion by tracking the dynamics and the fate of individual drops within the emulsion. At the slow flow limit of the concentrated emulsion, we observe an unexpected order, where the velocity of individual drops in the emulsion exhibits spatiotemporal periodicity. As the flow rate increases, the emulsion transitions from a solid-like to a liquid-like material, and the spatiotemporal order in the flow is lost. At the fast flow limit, droplet breakup starts to occur. We show that droplet breakup within the emulsion follows a probability distribution, in stark contrast to the deterministic behavior in classical single-drop studies. In addition to capillary number and viscosity ratio, break-up probability is governed by a confinement factor that measures drop size relative to a characteristic channel length. The breakup probability arises from the time-varying packing configuration of the drops. Finally, we discuss recent progress in computation methods for recapitulating the flow of concentrated emulsions., Comment: 58 pages, 14 figures

Autonomous systems have played an important role in response to the Covid-19 pandemic. Notably, there have been multiple attempts to leverage Unmanned Aerial Vehicles (UAVs) to disinfect surfaces. Although recent research suggests that surface transmission is less significant than airborne transmission in the spread of Covid-19, surfaces and fomites can play, and have played, critical roles in the transmission of Covid-19 and many other viruses, especially in settings such as child daycares, schools, offices, and hospitals. Employing UAVs for mass spray disinfection offers several potential advantages, including high-throughput application of disinfectant, large scale deployment, and the minimization of health risks to sanitation workers. Despite these potential benefits and preliminary usage of UAVs for disinfection, there has been little research into their design and effectiveness. In this work, we present an autonomous UAV capable of effectively disinfecting indoor surfaces. We identify relevant parameters such as disinfectant type and concentration, and application time and distance required of the UAV to disinfect high-touch surfaces such as door handles. Finally, we develop a robotic system that enables the fully autonomous disinfection of door handles in an unstructured and previously unknown environment. To our knowledge, this is the smallest untethered UAV ever built with both full autonomy and spraying capabilities, allowing it to operate in confined indoor settings, and the first autonomous UAV to specifically target high-touch surfaces on an individual basis with spray disinfectant, resulting in more efficient use of disinfectant

We combine theory, numerical simulation and experiments to investigate the breakup of two identical droplets entering a Y-junction with controlled spatial offset by which the second droplet trails the first. Based on fully resolved 3D simulations, we describe the flow physics leading to breakup. Scaling arguments, numerical simulation and experiments consistently show that for small initial offset, breakup always occurs with the droplet fragment volume depending linearly on the offset. Above a critical offset, which increases with the capillary number, the droplets enter the constriction sequentially without breakup. Our results are relevant for understanding the breakup behavior in a dense emulsion flowing through a linearly converging channel leading to a constriction. Such geometry is commonly used for the serial interrogation of droplet content in droplet microfluidic applications, where droplet breakup can limit the maximum throughput for such process. For capillary numbers up to $Ca\simeq10^{-2}$, the results from the two-droplet system in a Y-junction are consistent with breakup observations in dense emulsions flowing through a linearly converging channel. The deterministic relation between initial offset and resulting breakup in the two-droplet system suggests that the stochasticity that is observed in the breakup of a dense emulsion arises from multi-droplet interactions. The numerical value of the prefactor in the linear relation between initial offset and droplet fragment volume determined from experiments differs slightly from the one extracted from fully resolved numerical simulations. This discrepancy suggests that even at very high bulk surfactant concentrations, the rate-limiting surfactant adsorption kinetics allows for Marangoni stresses to develop and modify the droplet dynamics.

We present the design, fabrication and characterization of high-\emph{Q} (\emph{Q}=36,000) polymeric photonic crystal nanobeam cavities made of two polymers that have an ultra-low index contrast (ratio=1.15) and observed thermo-optical bistability at hundred microwatt power level. Due to the extended evanescent field and small mode volumes, polymeric nanobeam cavities are ideal platform for ultra-sensitive biochemical sensing. We demonstrate that these sensors have figures of merit (FOM=9190) two orders of magnitude greater than surface plasmon resonance based sensors, and outperform the commercial Biacore$^{\mathrm{TM}}$ sensors. The demonstration of high-Q cavity in low-index-contrast polymers can open up versatile applications using a broad range of functional and flexible polymeric materials.