Micromachines最新文献

{"title":"Towards the Optimization of Apodized Resonators.","authors":"Ana Valenzuela-Pérez, Carlos Collado, Jordi Mateu","doi":"10.3390/mi16050511","DOIUrl":"https://doi.org/10.3390/mi16050511","url":null,"abstract":"<p><p>Bulk Acoustic Wave (BAW) resonators are essential components in modern RF communication systems due to their high selectivity and quality factor. However, spurious resonances caused by Lamb wave mode propagation along the in-plane directions degrade the filter performance. Traditional Finite Element Method (FEM) simulations provide accurate modeling but are computationally expensive, especially for arbitrarily shaped resonators and solidly mounted resonators (SMRs), whose stack of materials is composed of many thin layers of different materials. To address this, we extend a previously published model (named the Quasi-3D model), which employs the Transmission Line Matrix (TLM) method, enabling efficient simulations of complex geometries with more precise meshing. The new approach allows us to simulate different geometries, and we will show several apodized geometries with the aim of minimizing the lateral modes. In addition, the proposed approach significantly reduces the computational cost while maintaining high accuracy, as validated by FEM comparisons and experimental measurements.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the Degradation and Failure Mechanisms of the Unclamped-Inductive-Switching Characteristics of p-GaN HEMT Devices.","authors":"Li Liu, Yulu Zhen, Siqiao Li, Bo Pang, Kai Zeng","doi":"10.3390/mi16050514","DOIUrl":"https://doi.org/10.3390/mi16050514","url":null,"abstract":"<p><p>Single UIS and repetitive UIS experiments are performed in this article to expound physical failure mechanisms in P-GaN HEMT devices. V_peak and I_peak are used as metrics to evaluate the degradation of electrical parameters. In the single UIS tests, different load inductors, off-gate voltages, and ambient temperatures are chosen as variables to observe the failure phenomena in the device under test (DUT), while in the repeated UIS tests, the threshold voltage, on-state resistance, blocking characteristics, and gate leakage current degradation and recovery are analyzed, and it is concluded that Vth presents a negative shift, R_on and BV are restored to their initial value, and gate leakage shows a significant reduction at first and then, after a duration of lagging, gradually recovers to some extent, but is unable to achieve its initial value. Combining failure point analysis via decapping with TCAD simulation and validation, it is found that hole trapping and detrapping in the p-GaN region dominate Vth and Igss degradation, while electron traps in the buffer dominate R_on and BV degradation.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensorless Impedance Control of Micro Finger Using Coprime Factorization.","authors":"Yuuki Morohoshi, Mingcong Deng","doi":"10.3390/mi16050510","DOIUrl":"https://doi.org/10.3390/mi16050510","url":null,"abstract":"<p><p>Soft robots are attracting attention as next-generation robots because they enable flexible movement. The micro finger is a soft robot that can bend and is small and can grasp objects of various shapes, so it is expected to be applied to surgical robots. However, because it is small, sensors cannot be attached, making it difficult to measure force. This paper proposes impedance control of the tip of a micro finger by estimating the tip force with an observer. The control system is designed using coprime factorization and Youla-Kucera parameterization by operator theory. The effectiveness of the proposed method is confirmed through experiments.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YOLO-SUMAS: Improved Printed Circuit Board Defect Detection and Identification Research Based on YOLOv8.","authors":"Ying Tang, Runhao Liu, Sheng Wang","doi":"10.3390/mi16050509","DOIUrl":"https://doi.org/10.3390/mi16050509","url":null,"abstract":"<p><p>Aiming at the demand for defect detection accuracy and efficiency under the trend of high-density and integration in printed circuit board (PCB) manufacturing, this paper proposes an improved YOLOv8n model (YOLO-SUMAS), which enhances detection performance through multi-module collaborative optimization. The model introduces the SCSA attention mechanism, which improves the feature expression capability through spatial and channel synergistic attention; adopts the Unified-IoU loss function, combined with the dynamic bounding box scaling and bi-directional weight allocation strategy, to optimize the accuracy of high-quality target localization; integrates the MobileNetV4 lightweight architecture and its MobileMQA attention module, which reduces the computational complexity and improves the inference speed; and combines ASF-SDI Neck structure with weighted bi-directional feature pyramid and multi-level semantic detail fusion to strengthen small target detection capability. The experiments are based on public datasets, and the results show that the improved model achieves 98.8% precision and 99.2% recall, and mAP@50 reached 99.1%, significantly better than the original YOLOv8n and other mainstream models. YOLO-SUMAS provides a highly efficient industrial-grade PCB defect detection solution by considering high precision and real-time performance while maintaining lightweight characteristics.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Thermal Conductivity of Nanoparticle-Doped Cutting Fluid Oils Using Feedforward Artificial Neural Networks (FFANN).","authors":"Beytullah Erdoğan, Abdulsamed Güneş, İrfan Kılıç, Orhan Yaman","doi":"10.3390/mi16050504","DOIUrl":"https://doi.org/10.3390/mi16050504","url":null,"abstract":"<p><p>Machining processes often face challenges such as elevated temperatures and wear, which traditional cutting fluids are insufficient to address. As a result, solutions involving nanoparticle additives are being explored to enhance cooling and lubrication performance. This study investigates the effect of thermal conductivity, an important property influenced by the densities of mono and hybrid nanofluids. To this end, various nanofluids were prepared by incorporating hexagonal boron nitride (hBN), zinc oxide (ZnO), multi-walled carbon nanotubes (MWCNTs), titanium dioxide (TiO₂), and aluminum oxide (Al₂O₃) nanoparticles into sunflower oil as the base fluid. Hybrid nanofluids were created by combining two nanoparticles, including ZnO + MWCNT, hBN + MWCNT, hBN + ZnO, hBN + TiO₂, hBN + Al₂O₃, and TiO₂ + Al₂O₃. A dataset consisting of 180 data points was generated by measuring the thermal conductivity and density of the prepared nanofluids at various temperatures (30-70 °C) in a laboratory setting. Conducting thermal conductivity measurements across different temperature ranges presents significant challenges, requiring considerable time and resources, and often resulting in high costs and potential inaccuracies. To address these issues, a feedforward artificial neural network (FFANN) method was proposed to predict thermal conductivity. Our multilayer FFANN model takes as input the temperature of the experimental environment where the measurement is made, the measured thermal conductivity of the relevant nanoparticle, and the relative density of the nanoparticle. The FFANN model predicts the thermal conductivity value linearly as output. The model demonstrated high predictive accuracy, with a reliability of R = 0.99628 and a coefficient of determination (R²) of 0.9999. The average mean absolute error (MAE) for all hybrid nanofluids was 0.001, and the mean squared error (MSE) was 1.76 × 10^-6. The proposed FFANN model provides a State-of-the-Art approach for predicting thermal conductivity, offering valuable insights into selecting optimal hybrid nanofluids based on thermal conductivity values and nanoparticle density.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimising (Al,Ga) (As,Bi) Quantum Well Laser Structures for Reflectance Mode Pulse Oximetry.","authors":"Aivaras Špokas, Andrea Zelioli, Andrius Bičiūnas, Bronislovas Čechavičius, Justinas Glemža, Sandra Pralgauskaitė, Mindaugas Kamarauskas, Virginijus Bukauskas, Janis Spigulis, Yi-Jen Chiu, Jonas Matukas, Renata Butkutė","doi":"10.3390/mi16050506","DOIUrl":"https://doi.org/10.3390/mi16050506","url":null,"abstract":"<p><p>We explore quantum well laser diodes for applications in pulse oximetry based on two material systems, namely, classical AlGaAs and a rather exotic GaAsBi, with lasing at around 800 nm and 1100 nm, respectively. These spectral regions and material families were selected due to their closely matched effective penetration depths into soft tissue. An improved design of the band structure of device active areas was tested on both material systems, yielding enhancement of the two main parameters, namely, output power and threshold current. A maximum emission power of the AlGaAs laser diode was registered at 4.9 mW (I = 60 mA, λ = 801 nm). For the GaAsBi-based devices, the target emission of 1106 nm was measured in pulsed mode with a peak output power of 9.4 mW (I = 3 A). The most optimized structure was based on three GaAsBi quantum wells surrounded by parabolically graded AlGaAs barriers. This structure was capable of 130 mW peak power (I = 2 A, λ = 1025 nm) along with a more than tenfold decrease in threshold current to 250 mA compared to a classical rectangular quantum well active region.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of Anti-Reflective Composite Structures on Inverted Pyramids Using Inductively Coupled Plasma Etching.","authors":"Zhiwei Fan, Liang Xu, Biyun Zhou, Tao Chen","doi":"10.3390/mi16050503","DOIUrl":"https://doi.org/10.3390/mi16050503","url":null,"abstract":"<p><p>The anti-reflective properties of silicon surfaces play a pivotal role in determining the light absorption efficiency of various silicon-based optoelectronic devices, with surface micro-nanostructures emerging as a crucial technological approach for achieving enhanced anti-reflection. In this study, inverted pyramid structures were employed as the micron-scale framework, and micro-nano composite structures were successfully prepared using an inductively coupled plasma (ICP) etching system. This paper, mainly focused on the micro-nano fabrication, investigated the effects of gas flow rate ratio (SF₆:O₂:C₄F₈), ICP power, RF power, and etching time on the surface morphology and reflectance of the composite structures. The results demonstrate that the optimal anti-reflective micro-nano composite structure was achieved under the following conditions: SF₆ flow rate of 18 sccm, O₂ flow rate of 9 sccm, C₄F₈ flow rate of 4 sccm, ICP power of 300 W, RF power of 5 W, and etching time of 5 min. The average reflectivity of the prepared surface structure was as low as 1.86%.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of the Coating Layers Deposited onto Curved Surfaces Using a Novel Multi-Nozzle Extrusion Printer.","authors":"Ramses Seferino Trigo Torres, Lawrence Kulinsky, Arash Kheradvar","doi":"10.3390/mi16050505","DOIUrl":"https://doi.org/10.3390/mi16050505","url":null,"abstract":"<p><p>Over the past two decades, additive manufacturing has advanced significantly, enabling rapid fabrication of functional components across various applications. In medical devices, it has been used for prototyping, prosthetics, drug delivery platforms, and more recently, tissue scaffolding. However, current technologies face challenges, particularly in depositing conformal layers over curved surfaces. This study introduces a novel multi-nozzle extrusion printer concept designed to deposit soft gel layers onto curved surfaces. A custom clearance locking mechanism enhances the printer's ability to achieve conformal coatings on both flat and curved substrates. We investigate key deposition parameters, including displacement volume and nozzle configuration, while comparing two deposition sequences: \"Press and Express\" and \"Express and Press\". Our results demonstrate that the \"Express and Press\" technique yields more uniform, merged conformal layers than the \"Press and Express\" method. This technology holds promise for further refinement and potential applications in tissue engineering.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM.","authors":"Hongqiao Huang, Wen Ye, Li Liu, Wenjing Wang, Yan Wang, Huiliang Cao","doi":"10.3390/mi16050507","DOIUrl":"https://doi.org/10.3390/mi16050507","url":null,"abstract":"<p><p>This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. Then, TVFEMD decomposes the gyroscope output signal into a series of product function (PF) signals and a residual signal. Next, sample entropy (SE) is employed to classify the decomposed signals into three categories: noise segment, mixed segment, and feature segment. According to the parallel model structure, the noise segment is directly discarded. Meanwhile, time-frequency peak filtering (TFPF) is applied to denoise the mixed segment, while the feature segment undergoes compensation. For compensation, the football team training algorithm (FTTA) is used to optimize the parameters of the long short-term memory (LSTM) neural network, forming a novel FTTA-LSTM architecture. Both simulations and experimental results validate the effectiveness of the proposed algorithm. After processing the MEMS gyroscope output signal using the PSO-TVFEMD-SE-TFPF denoising algorithm and the FTTA-LSTM temperature drift compensation model, the angular random walk (ARW) of the MEMS gyroscope is reduced to 0.02°/√h, while the bias instability (BI) decreases to 2.23°/h. Compared to the original signal, ARW and BI are reduced by 99.43% and 97.69%, respectively. The proposed fusion-based temperature compensation method significantly enhances the temperature stability and noise performance of the gyroscope.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of a Spiral Microfluidic Chip for the Mass Production of Lipid Nanoparticles Using Laser Engraving.","authors":"Inseong Choi, Mincheol Cho, Minseo Song, Byeong Wook Ryu, Bo Mi Kang, Joonyeong Kim, Tae-Kyung Ryu, Sung-Wook Choi","doi":"10.3390/mi16050501","DOIUrl":"https://doi.org/10.3390/mi16050501","url":null,"abstract":"<p><p>A spiral microfluidic chip (SMC) and multi-spiral microfluidic chip (MSMC) for lipid nanoparticle (LNP) production were fabricated using a CO₂ laser engraving method, using perfluoropolyether (PFPE) and poly(ethylene glycol) diacrylate as photopolymerizable base materials. The SMC includes a spiral microchannel that enables rapid fluid mixing, thereby facilitating the production of small and uniform LNPs with a size of 72.82 ± 24.14 nm and a PDI of 0.111 ± 0.011. The MSMC integrates multiple parallel SMC structures, which enables high-throughput LNP production without compromising quality and achieves a maximum production capacity of 960 mL per hour. The LNP fabrication technology using SMC and MSMC has potential applications in the pharmaceutical field due to the ease of chip fabrication, the simplicity and cost-effectiveness of the process, and the ability to produce high-quality LNPs.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144160095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}