Micro and Nano Systems Letters最新文献

Unique self-assembled germanium structures known as Germanium-on-Nothing (GON), which are fabricated via annealing, have buried multiscale cavities with different morphologies. Due to their unique sub-surface morphologies, GON structures are utilized in various applications including optoelectronics, micro-/nanoelectronics, and precision sensors. Each application requires different cavity shapes, and a simulation tool is able to determine the required annealing duration for a given shape. However, a theoretical simulation inevitably requires simplifications which limit its accuracy. Herein, to resolve such dependence on simplification, we introduce a deep learning-based method for simulating the transformation of sub-surface morhpology of GON over annealing. Namely, a deep learning model is trained to predict GON’s morphological transformation from 4 cross-sectional images acquired at different annealing times. Compared to conventional simulation schemes, our proposed deep learning-based simulation method is not only computationally efficient ((sim 10) min) but also physically accurate with its use of empirical data.

Silicon bulk micromachining is extensively employed method in microelectromechanical systems (MEMS) for the formation of freestanding (e.g., cantilevers) and fixed (e.g., cavities) microstructures. Wet anisotropic etching is a popular technique to perform silicon micromachining as it is low-cost, scalable, and suitable for large scale batch processing, which are the major factors considered in the industry to reduce the cost of the product. In this work, we report the wet anisotropic etching characteristics of Si{111} in sodium hydroxide (NaOH) without and with addition of hydroxylamine (NH₂OH). 10M NaOH and 12% NH₂OH are used for this study. The effect of NH₂OH is investigated on the etch rate, etched surface roughness and morphology, and the undercutting at mask edges aligned along < 112 > direction. These are the major etching characteristics, which should be studied in a wet anisotropic etchant. A 3D laser scanning microscope is utilized to measure the surface roughness, etch depth, and undercutting length, while the etched surface morphology is examined using a scanning electron microscope (SEM). The incorporation of NH₂OH in NaOH significantly enhances the etch rate and the undercutting at the mask edges that do not consist of {111} planes. To fabricate freestanding structure (e.g., microcantilever) on Si{111} wafer, high undercutting at < 112 > mask edges is desirable to reduce the release time. Moreover, the effect of etchant age on the abovementioned etching characteristics are investigated. The etch rate and undercutting reduce significantly with the age of the modified NaOH. The present paper reports very interesting results for the applications in wet bulk micromachining of Si{111}.

The separation of biological cells or microorganisms in a liquid based on their size by deterministic lateral displacement is widely used in laboratories. The analytical equation for the critical diameter is derived under the assumption that flow between two posts is better described by flow in a rectangular tube than between parallel plates. The height position of the particle is an additional parameter that affects the critical diameter. Preliminary experiments were carried out on the separation of particles in deep and shallow microchannels. This study shows that the critical diameter is not a constant value for a given design but is different on each plane parallel to the top and bottom of the channel. The theoretical model was used to analyze experimental data on the separation of particles larger than 4.2 µm from particles ranging in size from 2.5 to 7.9 µm.

Neural interfaces are fundamental tools for transmitting information from the nervous system. Research on the immune response of an invasive neural interface is a field that requires continuous effort. Various efforts have been made to overcome or minimize limitations through modifying the designs and materials of neural interfaces, modifying surface characteristics, and adding functions to them. In this study, we demonstrate microfluidic channels with crater-shaped structures fabricated using parylene-C membranes for fluid delivery from the perspective of theory, design, and simulation. The simulation results indicated that the fluid flow depended on the size of the outlet and the alignment of microstructures inside the fluidic channel. All the results can be used to support the design of microfluidic channels made by membranes for drug delivery.

Multiple lesions in the same vessel is one of the most common situations found in patients suffering from cardiovascular diseases, this complicates not only the assessment of the severity of each one but also their treatment. To date, the effect of multiple stenoses on different parameters has been simulated by numerical studies. Few others have implemented in vitro platforms for their investigation. However, visualization of thrombosis formation in this kind of lesion is still needed. This in vitro study monitors the formation of thrombus inside microchannels having one, two, and three stenoses. Whole blood was perfused through each channel at high shear rates (> 12,000 s⁻¹), generating thrombosis. Flow changes across each lesion as well as the final percentage of aggregations were monitored. Thus, the location where total occlusion could be produced was found to be the first stenosis for all the cases. Less flow reaching the second and third stenoses was observed which demonstrates that aggregations were growing at the first one. This was verified by measuring the percentage of aggregations at the end of the test.

The development of high-performance strain sensors has attracted significant attention in the field of smart wearable devices. However, stretchable strain sensors usually suffer from a trade-off between sensitivity and sensing range. In this study, we investigate a highly sensitive and stretchable piezoresistive strain sensor composed of a hybrid film of 1D multi-walled carbon nanotube (MWCNT) and 2D graphene that forms a percolation network on Ecoflex substrate by spray coating. The mass of spray-coated MWCNT and graphene and their mass ratio are modulated to overcome the trade-off between strain sensitivity and sensing range. We experimentally found that a stable percolation network is formed by 0.18 mg of MWCNTs (coating area of 200 mm²), with a maximum gauge factor (GF) of 1,935.6 and stretchability of 814.2%. By incorporating the 0.36 mg of graphene into the MWCNT film (i.e., a mass ratio of 1:2 between MWCNT and graphene), the GF is further improved to 12,144.7 in a strain range of 650–700%. This high GF is caused by the easy separation of the graphene network under the applied strain due to its two-dimensional (2D) shape. High stretchability originates from the high aspect ratio of MWCNTs that bridges the randomly distributed graphenes, maintaining a conductive network even under sizeable tensile strain. Furthermore, a small difference in work function between MWCNT and graphene and their stable percolation network enables sensitive UV light detection even under a significant strain of 300% that cannot be achieved by sensors composed of MWCNT- or graphene-only. The hybrids of MWCNT and graphene provide an opportunity to achieve high-performance stretchable devices.

To overcome the limitations of muscle-based prostheses, studies on nerve-based prostheses for sensory feedback have recently been reported. To develop such prostheses, intrafascicular electrodes, a type of peripheral nerve interface, are essentially used to connect the nervous system and external systems. Through these electrodes, sensory feedback to induce sensations in patients is possible. To evoke natural sensations, precise recordings of nerve signals should precede sensory feedback, in order to identify patterns of sensory signals in the nerve and to mimic these patterns in stimulating the nerve. For this purpose, we previously developed a PDMS-based flexible penetrating microelectrode array (FPMA). In the current study, we verified the ability of the FPMA to record sensory nerve signals. The FPMA implanted in the rabbit sciatic nerve was able to record spontaneous neural signals, and the recorded signals were separated into action potential units. In addition, sensory nerve signals synchronized with ankle movement were successfully recorded, demonstrating that the FPMA is a useful peripheral neural interface capable of recording high-resolution sensory signals.

In this study, a pneumatic dispenser driven by a flexible membrane with a capacitive-type sensor using an SLA-type 3D printer was fabricated. It was confirmed that a single droplet in the range of approximately 400–450 nL could be ejected from the current processed 200-μm-diameter nozzle. The deformation varied according to the magnitude and time of the positive pressure applied to the membrane sensor. In addition, the signals of the normal dispensing and abnormal states, in which the solution was not ejected when the inlet pressure was removed, were measured and compared. The base capacitance-to-digital converter (CDC) value decreased when the inlet pressure was removed. Thus, it was able to confirm the feasibility of monitoring the normal and abnormal ejection status of the pneumatic dispenser.

Extracellular vesicles (EVs) are nano-sized vesicles derived from cells that transport biomaterials between cells through biofluids. Due to their biological role and components, they are considered as potential drug carriers and for diagnostic applications. Today's advanced nanotechnology enables single-particle-level analysis that was difficult in the past due to its small size below the diffraction limit. Single EV analysis reveals the heterogeneity of EVs, which could not be discovered by various ensemble analysis methods. Understanding the characteristics of single EVs enables more advanced pathological and biological researches. This review focuses on the advanced techniques employed for EV analysis at the single particle level and describes the principles of each technique.

Metal oxide-based sensors have been widely used to detection biomarkers in exhaled breath for identification of various diseases such as asthma, diabetes, halitosis, and lung cancer. Herein, we proposed one step hydrothermal method for the preparation of SnO₂ nanospheres and reduced graphene oxide incorporated SnO₂ nanospheres for the detection of two important biomarkers such as decane and heptane from the exhaled breath of lung cancer patients. The as prepared materials are investigated in detail through various analytical techniques and the findings are consistent with each other. The sensing response of the proposed sensors were systematically investigated to enhance their sensing performance as a function of operating temperatures and gas concentration, and different analyte gases. The sensors showed maximum sensing response toward heptane and decane compared to other interfering gases such as hydrogen, carbon monoxide, acetone, ethanol, and methanol at 125 °C. The proposed sensors exhibit excellent detection range as low as 1 ppm with appreciably fast response and recovery time. Lung cancer patients may be easily screened using the proposed sensor, by detecting decane and heptane in their exhaled breath.