Micromachines最新文献

This review summarizes the use of Auger Electron Spectroscopy (AES) for microchemical analysis of two different types of dielectric/(Al,Ga)N-based systems: (i) extrinsic dielectric PECVD SiO₂, ALD Al₂O₃, and ECR-CVD SiN_x films on Al_xGa_1-xN/GaN structures in the context of their application in microelectronic power devices and (ii) intrinsic Al₂O₃ films on AlN epitaxial layers grown by high-temperature oxidation for nanostructured technology of various gas/ion sensors. Particular attention is given to AES depth profiling across complete multilayer cross-sections, combining qualitative analysis of spectral line shape and intensity evolution as well as kinetic energy shifts with quantitative elemental depth distributions. This approach enables identification of chemical states and oxidation-related transformations at dielectric/semiconductor interfaces. Reported results demonstrate that AES provides micro- to nanometer-scale chemical information essential for distinguishing interfacial from the bulk properties. The capabilities and inherent limitations of AES depth profiling, including sputter-induced artifacts are also addressed, highlighting the role of optimized experimental conditions in reliable interface analysis.

This paper describes the radio-frequency (RF) characteristics of stacked metal-insulator-metal (MIM) capacitors used in RF CMOS technology. To ensure accurate analysis, various de-embedding methods for stacked MIM capacitors were verified, and an improved RF model was constructed accordingly. To develop an equivalent circuit for the improved RF model by analyzing the RF characteristics of stacked MIM capacitors, we compared de-embedding methods for measured stacked MIM capacitors: one-step (open-pattern or short-pattern) de-embedding and two-step (combined open-pattern and short-pattern) de-embedding. For the analysis of stacked MIM capacitors, at least two-step de-embedding was used, while for precise de-embedding, three-step de-embedding using a thru pattern was employed. Based on the measured values obtained using these two-step de-embedding methods, a modified equivalent circuit was constructed. This circuit was analyzed based on various parameters, including MIM capacitance, quality factor, S-parameter, and Y-parameter, and the results were comparatively examined. The findings highlight outstanding accuracy of the modified model, which is maintained even in high frequency bands.

In this paper, the impact of negative bias temperature instabilities (NBTIs) on commercial power p-channel Vertical Double-Diffused MOS (VDMOS) transistors from the standpoint of practical applications was analyzed. The effects of NBTI are one of the main reliability concerns for this type of device, so it is necessary to investigate how these effects influence various applications. A series of experiments were carried out including negative bias temperature stressing, infra-red thermographic recording and circuit characterization, with the goal of evaluating the effects of negative bias temperature stressing on the self-heating of samples in load-driving circuits operating with higher currents and circuit performance of a CMOS inverter circuit containing the examined samples. The findings suggest that negative bias temperature stressing-induced threshold voltage shift directly affects increased self-heating in load-driving circuits and that it also directly affects transfer and dynamics characteristics in CMOS inverters.

This study presents a comprehensive systematic analysis, investigating hardware accelerators specifically designed for real-time cardiovascular signal processing, focusing mainly on Electrocardiogram (ECG), Photoplethysmogram (PPG), and blood pressure monitoring systems. Cardiovascular Diseases (CVDs) represent the world's leading cause of morbidity and mortality, creating an urgent demand for efficient and accurate diagnostic technologies. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically analysed 59 research papers on this topic, published from 2014 to 2024, categorising them into three main categories: signal denoising, feature extraction, and decision support with Machine Learning (ML) or Deep Learning (DL). A comprehensive performance benchmarking across energy efficiency, processing speed, and clinical accuracy demonstrates that hybrid Field Programmable Gate Array (FPGA)-Application Specific Integrated Circuit (ASIC) architectures and specialised Artificial Intelligence (AI) on Edge accelerators represent the most promising solutions for next-generation CVD monitoring systems. The analysis identifies key technological gaps and proposes future research directions focused on developing ultra-low-power, clinically robust, and highly scalable physiological signal processing systems. The findings provide guidance for advancing hardware-accelerated cardiovascular diagnostics toward practical clinical deployment.

This paper presents a novel lightweight fabric strain sensor array specifically designed for comprehensive knee joint monitoring. The sensor system features a unique two-layer design incorporating eight strategically positioned sensing elements, enabling effective spatial mapping of strain distribution across the knee during movement. This configuration offers advantages in capturing complex multi-axis kinematics (flexion/extension, rotation) and localized tissue deformation when compared to simpler sensor layouts. To evaluate the system, ten subjects performed three distinct activities (seated leg raise, standing, walking), generating resistance data from the sensors. A hybrid deep learning model (CNN + BiLSTM + Attention) processed the data and significantly improved performance to 95%. This enhanced accuracy is attributed to the model's ability to extract spatial-temporal features and leverage long-term dependencies within the time-series sensor data. Furthermore, channel attention analysis within the deep learning model identified sensors 2, 4, and 6 as major contributors to classification performance. The results demonstrate the feasibility of the proposed fabric sensor array for accurately recognizing fundamental knee movements. Despite limitations in the diversity of postures, this system holds significant promise for future applications in rehabilitation monitoring, sports science analytics, and personalized healthcare within the medical and athletic domains.

This paper introduces an enhanced bandgap reference (BGR) design, addressing the shortcomings of traditional circuits, such as significant temperature drift, limited power-supply rejection, and inadequate load-driving capacity. The proposed design incorporates a symmetric folded common-emitter-common-base BJT amplifier with MOS-assisted biasing, employed in the proposed BGR, enforcing branch voltage symmetry to effectively suppress intrinsic offset caused by structural mismatch. By reducing the amplifier input offset, the circuit achieves improved reference voltage stability, a lower temperature coefficient (TC), and an enhanced power-supply rejection ratio (PSRR). Additionally, a negative-feedback adaptive current-adjustment driver is implemented to dynamically adjust the output current in response to real-time load changes. This method bolsters the load-driving capability and maintains a stable reference output across varying load conditions. The circuit was simulated using a 0.18 μm BCD process, revealing that with a 3.3 V supply voltage, the BGR produces a stable output voltage of 2.5 V, with a TC of 2.372×10-6 °C^-1. The simulated PSRR is -114.2 dB at DC and -62.07 dB at 1 kHz. Moreover, under a 3.3 V supply, sweeping the load capacitance from 0.1 μF to 100 μF demonstrates that the reference voltage remains consistently regulated at 2.5 V, confirming its excellent load tolerance and output stability.

This study reports the development of paclitaxel (PTX)-loaded human serum albumin (HSA) nanoparticles (NPs), surface-decorated with trastuzumab (TMAB), with potential applicability in HER2-oriented delivery. The NPs were obtained via thermally driven self-assembly followed by non-covalent antibody adsorption and they were characterized using Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), and ζ-potential analysis. The drug association efficiency (%DAE), defined exclusively for PTX, was high for both HSA-PTX and HSA-PTX-TMAB NPs (96.4% and 98.2% w/w, respectively), with loading capacities (%LC) of 8.9% and 7.4%, respectively. TMAB decoration led to a modest increase in mean diameter and a reduction in surface charge, consistent with successful surface modification. Both formulations exhibited rapid early-phase PTX release followed by an apparent stabilization phase, with distinct kinetic behavior between HSA-PTX and HSA-PTX-TMAB NPs. Cytotoxicity in A549 cells after 18 h of exposure showed modest, non-differential effects consistent with controlled release and short-term assessment of non-specific toxicity. Overall, this thermally assembled albumin-based system provides a promising foundation for further evaluation of HER2-oriented PTX delivery.

Electron beam powder bed fusion (EB-PBF) Ti6Al4V often exhibits high vertical surface roughness, limiting its use in high-end applications. In this study, an infrared continuous-wave laser was applied to precisely polish the vertical surface. An orthogonal design identified the optimal condition as 10,400 kW/cm² power density, 800 mm/s scanning speed, and one pass, achieving a minimum Sa of 0.24 μm and a 98.03% reduction compared with the as-built surface. To address the adhered semi-molten particle characteristics of EB-PBF sidewalls, a molten-pool-dynamics-based polishing model was developed and validated, yielding an error as low as 1.24%. Simulations indicate that power density governs the final morphology by controlling molten pool coverage, scanning speed affects polishing efficiency via thermocapillary force, and polishing time influences surface quality by triggering or avoiding melt splashing.

Solid rocket motors (SRMs) play a pivotal role in space exploration owing to their reliability and high thrust-to-weight ratios. SRM propellant health monitoring is in critical demand owing to the complex operational scenarios throughout the entire life cycle of SRMs. To achieve in situ detection of three-dimensional stress, this study introduces a novel flexible three-dimensional stress sensor (FSS). First, a liquid metal pressure-sensing element with a variable cross-section was designed and numerically modeled. The performance of the FSS under different loading conditions was analyzed using finite element modeling. The sensing element prototype was fabricated using mold casting and liquid metal injection methods. The fabricated sensing-element prototype with an area ratio of 1:5 exhibited a sensitivity coefficient of 1.5%/kPa at a pressure of 300 kPa, a maximum hysteresis error of 3.98%, and a stability error of 0.17%. Finally, the FSS was developed by integrating multiple pressure-sensing elements and encapsulating the force-concentrating layers. The fabricated FSS prototype was characterized using simulated propellant experiments. Via comparison with the simulation results, the FSS was found to detect multiaxial stress differences when embedded within a propellant.

Light-controlled ion drag pumps have attracted considerable interest in soft robotics, biomedical engineering, and microelectromechanical systems (MEMS) due to their non-contact energy supply and high spatiotemporal controllability of light. However, experimental studies on their pumping performance and influencing factors remain limited. This study integrates the photoelectric effect with field emission phenomena to design and fabricate a light-controlled ion drag pump using lanthanum-modified lead zirconate titanate (PLZT) ceramic. The light-controlled pump enables non-contact energy transfer and fluid transport via high-energy laser irradiation. A series of experiments systematically investigate its pumping performance and key influencing factors. Results indicate that optimizing electrode structure and fluid channel design, along with increased light intensity, significantly enhances pumping performance. This work provides fundamental design guidelines for the application of light-controlled ion drag pumps in microfluidics, flexible robotics, and microdevice thermal management.