Micromachines最新文献

Sliding bearing alloy layers must combine excellent tribological performance with reliable metallurgical bonding, but conventional fabrication methods often suffer from coarse grains, chemical segregation and poor interface adhesion. Annular coaxial laser wire-feed cladding, by providing more uniform heat input and rapid solidification, is expected to mitigate these deficiencies; however, systematic studies of this technique applied to tin-based Babbitt alloy layers remain limited. In this work, Babbitt layers produced by conventional casting and by annular coaxial laser wire-feed cladding were compared in terms of microstructure, phase constitution, hardness and tribological behavior. The results indicate that laser cladding can produce continuous, dense and well-bonded coatings and markedly refine the SnSb phase, reducing grain size from approximately 100 μm in the cast material to 10-20 μm. Hardness increased from 25.3 HB to 27.6 HB, while tribological performance improved substantially: the coefficient of friction decreased by about 38.19% and the wear volume was reduced by approximately 10.46%. These improvements are attributed mainly to the rapid solidification, low dilution and more uniform phase distribution associated with annular coaxial laser cladding, demonstrating the strong potential of this process for fabricating high-performance tin-based Babbitt bearing layers.

This paper reports the results of a system-level total ionizing dose (TID) effect simulation study on a SMIC 130 nm LEON2 processor. Firstly, the device-level simulations of the 130 nm NMOS transistors are performed using the Sentaurus TCAD software to analyze the effects of a bias condition, channel width, and irradiation dose on a TID-induced leakage current. Based on the TCAD simulation results, a Verilog-A-based compact model is developed for NMOS transistors to describe the TID-induced leakage current, and it is then embedded into target nodes of the SPICE netlist for the LEON2 processor, enabling system-level TID simulations. The simulation results reveal the processor's failure threshold and corresponding failure mechanism; meanwhile, the increase in the power supply current with the irradiation dose is also observed. The research reported in this paper can provide beneficial guidance for radiation performance evaluation and radiation hardening by design (RHBD) in 130 nm bulk CMOS processors.

We experimentally and theoretically demonstrate coexistence of three different wavelength-multiplexed bound dual-frequency pulses in an all-fiber mode-locked fiber laser, effectively achieved by exploiting polarization-dependent loss effects and two uneven gain peaks of Er-doped fiber. With the single wall carbon-nanotube-based intensity modulation, wavelength-multiplexed dual-frequency pulses located at 1531.1 nm and 1556.6 nm are obtained. Changing the polarization rotation angles in the fiber cavity, one of the two asynchronous pulses evolves into a bound state of a doublet, in which the center wavelength of the bound solitons is centered at ~1530 nm or ~1556 nm. The relative phase between the two bound solitons or modulation depth of bound solitons can be switched by a polarization controller. A simulation method based on coupled Ginzburg-Landau equations is provided to characterize the laser physics and understand the mechanism behind the dynamics of tuning between different bound dual-frequency pulses. The proposed fiber laser will provide a potential way to understand multiple soliton dynamics and implementation in optical frequency combs generation.

In this study, a Metamaterial Incident Photon Reconstruction Theory (MIPRT) is developed to describe the modulation process of metamaterials on incident photons. The theory includes the Invariant Incident Photon Hypothesis and Resonant Phase Deconstruction and Quantification; it reveals the modulation characteristics of metamaterials on incident photons, not by first absorption and then re-emission but by inducing coherent destructive interference, which brings about redistribution of the spatial probability of photon occurrence. This theory is validated in a single-layer metamaterial, and a unique relationship between the resonant phase and amplitude is derived and confirmed by simulation. The proposed MIPRT brings a comprehensive understanding of the electromagnetic (EM) response characteristics of metamaterials and provides a new idea for metamaterial theory from another perspective.

In the process of in situ stress fracturing drilling in coal mines, obtaining downhole vibration data not only improves drilling efficiency but also plays a key role in ensuring operational safety. Nevertheless, the energy supply techniques used in current vibration detectors reduce operational performance and escalate excavation expenses. This research proposes a self-powered vibration sensor based on the triboelectric nanogenerator, designed for the operational environment of coal mine in situ stress fracturing drilling. It can simultaneously detect axial and lateral vibration frequencies, and the inclusion of redundant sensing units provides the sensor with high reliability. Experimental outcomes demonstrate that the device functions across a frequency span of 0 to 11 Hz, maintaining error margins for frequency and amplitude under 4%. Furthermore, it functions reliably in environments where temperatures are under 150 °C and humidity is under 90%, proving its strong resilience to environmental factors. In addition, the device possesses self-generating potential, achieving a maximum voltage of 68 V alongside an output current of 51 nA. When connected to a 6 × 10⁷ Ω load, the maximum output power can reach 3.8 × 10^-7 W. Unlike traditional subsurface oscillation detectors, the proposed unit combines self-generation capabilities with highly reliable measurement characteristics, making it more suitable for practical drilling needs.

Research on heat and mass transfer in microchannels represents the cutting-edge frontier in modern high-density electronic cooling, advanced energy systems, and precision microfluidic manipulation [...].

The development of photonic-integrated circuits (PICs) for data communication, sensing, and quantum computing is hindered by the high complexity and cost of traditional fabrication methods, which rely on expensive equipment, limiting accessibility for research and prototyping. This study introduces a Direct Laser Writing (DLW) system designed as a low-cost alternative, utilizing an XY platform for precise substrate movement and an optical system comprising a collimator and lens to focus the laser beam. Operating on a single layer, the system employs SU-8 photoresist to fabricate polymer-based structures on substrates such as ITO-covered glass. Preparation involves thorough cleaning, spin coating with photoresist, and pre- and post-baking to ensure material stability. This approach reduces dependence on costly infrastructure, making it suitable for academic settings and enabling rapid prototyping. A user interface and custom slicer process standard .dxf files into executable commands, enhancing operational flexibility. Experimental results demonstrate a resolution of 10 µm, with successful patterning of structures, including diffraction grids, waveguides, and multimode interference devices. This system aims to transform PIC prototype fabrication into a cost-effective, accessible process.

Silica spicules provide a natural transdermal conduit but require a linker that binds strongly under physiological conditions and releases payloads selectively in response to biological cues. Existing silane chemistries or polydopamine coatings lack enzyme responsiveness and show limited control over release. We created a 180-member peptide library with the motif L-X1-X2-[Y-F-Y]-A-L-G-P-H-C and screened for silica binding. Biophysical assays (circular dichroism, ζ-potential, quartz crystal microbalance, atomic force microscopy) and molecular dynamics identified high-affinity binders. The lead, P176, was tested for matrix metalloprotease (MMP)-responsive cleavage. Conjugation and release of Vitamin C and Stigmasterol were analyzed by HPLC and Franz diffusion cells. P176 showed high silica affinity (~55 µg mg^-1), robust biophysical signals (Δf -35 to -38 Hz; rupture force ~154 pN; ζ shift -22 to-11.5 mV), and favorable adsorption energy (-48.5 kcal mol^-1, contact 4.5 nm², 8.5 H-bonds). The MMP gate displayed efficient kinetics (Vmax 117.9 RFU·min^-1, Km 5.0 µM) with >90% cleavage at 60 min, reduced to 26% by inhibitor. Conjugation yields reached 87% (Vitamin C) and 77% (Stigmasterol). Franz diffusion showed MMP-dependent release (24 h: Vitamin C 90-96%, Stigmasterol 80-85%) with minimal basal leakage. Released Vitamin C enhanced collagen I to ~250% in fibroblasts, while Stigmasterol attenuated LPS-induced macrophage morphology; keratinocytes retained normal marker expression. This study demonstrates that a single amphipathic, sequence-programmed peptide can couple strong silica anchoring with protease-responsive release and broad payload compatibility, establishing a versatile platform for spicule-based transdermal and regenerative delivery.

Glass-insulated terminals (GITs) are widely used in high-reliability microelectronic systems, where glass fall-offs in the sealing region may seriously degrade the reliability of the microelectronic component and further degrade the device reliability. Automatic inspection of such defects is challenging due to strong light reflection, irregular defect appearances, and limited defective samples. To address these issues, a coarse-to-fine machine-learning framework is proposed for glass fall-off detection in GIT images. By exploiting the circular-ring geometric prior of GITs, an adaptive sector partition scheme is introduced to divide the region of interest into sectors. Four categories of sector features, including color statistics, gray-level variations, reflective properties, and gradient distributions, are designed for coarse classification using a gradient boosting decision tree (GBDT). Furthermore, a sector neighbor (SN) feature vector is constructed from adjacent sectors to enhance fine classification. Experiments on real industrial GIT images show that the proposed method outperforms several representative inspection approaches, achieving an average IoU of 96.85%, an F1-score of 0.984, a pixel-level false alarm rate of 0.55%, and a pixel-level missed alarm rate of 35.62% at a practical inspection speed of 32.18 s per image.

Micro-motors are widely used in industrial applications, which require effective fault diagnosis to maintain safe equipment operation. However, fault signals from micro-motors often exhibit weak signal strength and ambiguous features. To address these challenges, this study proposes a novel fault diagnosis method. Initially, the Jump plus AM-FM Mode Decomposition (JMD) technique was utilized to decompose the measured signals into amplitude-modulated-frequency-modulated (AM-FM) oscillation components and discontinuous (jump) components. The proposed process extracts valuable fault features and integrates them into a new time-domain signal, while also suppressing modal aliasing. Subsequently, a novel Global Relationship Matrix (GRM) is employed to transform one-dimensional signals into two-dimensional images, thereby enhancing the representation of fault features. These images are then input into an Optimized Convolutional Neural Network (OCNN) with an AdamW optimizer, which effectively reduces overfitting during training. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy rate of 99.0476% for multiple fault types, outperforming four comparative methods. This approach offers a reliable solution for quality inspection of micro-motors in a manufacturing environment.