Journal Description
Micromachines
Micromachines
is a peer-reviewed, open access journal on the science and technology of small structures, devices and systems, published monthly online by MDPI. The Chinese Society of Micro-Nano Technology (CSMNT) and AES Electrophoresis Society are affiliated with Micromachines and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Ei Compendex, dblp, and other databases.
- Journal Rank: JCR - Q2 (Instruments and Instrumentation) / CiteScore - Q1 (Mechanical Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.8 days after submission; acceptance to publication is undertaken in 1.9 days (median values for papers published in this journal in the second half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Micromachines.
- Companion journal: Micro.
- Journal Cluster of Instruments and Instrumentation: Actuators, AI Sensors, Instruments, Metrology, Micromachines and Sensors.
Impact Factor:
3.0 (2024);
5-Year Impact Factor:
3.1 (2024)
Latest Articles
Comprehensive Review of Research Progress on Trajectory Planning and Weld Seam Tracking in Wire Arc Additive Manufacturing
Micromachines 2026, 17(6), 698; https://doi.org/10.3390/mi17060698 (registering DOI) - 7 Jun 2026
Abstract
Wire arc additive manufacturing (WAAM) has emerged as a promising technology for producing large-scale metal components due to its high deposition efficiency, low material cost, and design flexibility. However, the widespread industrial adoption of WAAM is hindered by challenges in geometric accuracy, process
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Wire arc additive manufacturing (WAAM) has emerged as a promising technology for producing large-scale metal components due to its high deposition efficiency, low material cost, and design flexibility. However, the widespread industrial adoption of WAAM is hindered by challenges in geometric accuracy, process stability, and defect control, which are closely related to two critical aspects: trajectory planning and real-time weld seam tracking. This review provides a comprehensive and critical analysis of recent advances in both fields, with an emphasis on their interconnection rather than treating them as separate research streams. Unlike existing reviews that primarily summarize path planning algorithms or image processing techniques in isolation, this paper explicitly examines the integration challenges and synergistic potential between offline trajectory optimization and online vision-based monitoring. Key topics include adaptive path strategies for sharp corners and intersections, interlayer filling methods to mitigate heat accumulation and residual stress, as well as passive and active visual sensing technologies for molten pool characterization and defect detection. The review further identifies a persistent gap in closed-loop systems that combine real-time image feedback with dynamic path replanning. Based on the analysis of representative studies, current limitations are discussed and future research directions are proposed, including the development of digital twins, multi-modal data fusion, and reinforcement learning-based adaptive control. This review offers a distinct perspective aimed at advancing intelligent, high-precision WAAM systems for complex metal components.
Full article
(This article belongs to the Special Issue Advances in Additive Manufacturing Technologies for Architected Materials)
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Open AccessArticle
Miniaturized Wearable System for Multimodal EEG/ECG/EMG Sensing and Real-Time Physiological Monitoring
by
Yunxiang Zhang, Xueyang Meng, Chengbang Lu, Yingning He and Xiangyu Liang
Micromachines 2026, 17(6), 697; https://doi.org/10.3390/mi17060697 (registering DOI) - 6 Jun 2026
Abstract
Real-time physiological state awareness is central to next-generation wearable computing, yet most existing electrophysiological signal acquisition platforms remain limited to single-modality sensing, high component cost, or bulky form factors that hinder everyday deployment. Here, we present a compact, low-cost wearable platform for simultaneous
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Real-time physiological state awareness is central to next-generation wearable computing, yet most existing electrophysiological signal acquisition platforms remain limited to single-modality sensing, high component cost, or bulky form factors that hinder everyday deployment. Here, we present a compact, low-cost wearable platform for simultaneous electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) acquisition. The system integrates an analog front-end, a microcontroller, and a Bluetooth wireless link on a compact single-board platform (5.6 × 3.8 cm, approximately 12.8 g with the selected lithium-polymer battery installed), with an estimated bill-of-materials cost of 67.40 USD. Experimental validation across three healthy subjects, with the ECG channel additionally benchmarked against a commercial clinical-grade ambulatory ECG recorder, demonstrates that the platform captures ECG waveforms with recognizable P-QRS-T morphology under controlled recording conditions, supports reliable R-peak detection and heart rate estimation, records stable resting-state EEG spectral features, and distinguishes EMG activation from resting baseline in both time-domain amplitude and time-frequency structure. Leveraging the real-time wireless data link between the wearable hardware and a PC-hosted MATLAB environment, we further explore application-oriented signal processing scenarios. As an offline algorithm-pipeline compatibility demonstration, a CNN-based seizure detection pipeline is applied to the Bonn EEG benchmark for five-class epileptic state classification, achieving 86.60% mean classification accuracy. The proposed system offers a scalable and affordable foundation for wearable human-state-aware interaction, with potential applications in clinical monitoring, rehabilitation, and brain–computer interfaces.
Full article
(This article belongs to the Special Issue Bioelectronics and Its Limitless Possibilities)
Open AccessArticle
Magnetic Microspheres as Microrobot Bodies: Optimized Chitosan Modification and Gel Dispersion for Controlled Release of Doxorubicin
by
Shiqi Ma and Lizhong Xu
Micromachines 2026, 17(6), 696; https://doi.org/10.3390/mi17060696 (registering DOI) - 6 Jun 2026
Abstract
Although the loading and targeted release of drugs are core biomedical applications of micro-nano robots, they are restricted by the complexity of robot fabrication and drug loading/release regulation. This work adopts magnetic microspheres (MMs) as microrobot bodies, owing to their low driving resistance
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Although the loading and targeted release of drugs are core biomedical applications of micro-nano robots, they are restricted by the complexity of robot fabrication and drug loading/release regulation. This work adopts magnetic microspheres (MMs) as microrobot bodies, owing to their low driving resistance and ease of preparation, in order to explore the loading and release of anticancer drugs via physical adsorption and chitosan surface functionalization. Two modification routes, chitosan solution (CS) and chitosan colloid (CC), were compared in terms of their efficacy in fabricating magnetic chitosan microspheres (MCMs). The dispersion procedure of chitosan gel (CG)-encapsulated MMs was optimized to obtain microspheres with uniform size and good encapsulation. Doxorubicin (DOX) was used as a model drug, and the optimized microstructure exhibited high loading efficiency and excellent controlled release. This study offers a low-cost strategy to advance micro-nano robots toward targeted drug delivery applications.
Full article
(This article belongs to the Special Issue Micro-/Nanomotors: Design, Fabrication and Applications)
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Open AccessArticle
Experimental Research on ZnFe2O4@ZnCo2O4//AC@PANI Supercapacitor Energy Storage Devices for New Energy Vehicles Based on “Dual Carbon” Goals
by
Yifei Wang, Yang Wang, Qing Liu, Gengchen Li and Jing Wang
Micromachines 2026, 17(6), 695; https://doi.org/10.3390/mi17060695 (registering DOI) - 5 Jun 2026
Abstract
Driven by the “Dual Carbon” goals, supercapacitors have become critical energy storage devices for new energy electric vehicles. In this paper, a ZnFe2O4@ZnCo2O4 core–shell cathode was prepared by a hydrothermal method followed by high-temperature annealing, and
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Driven by the “Dual Carbon” goals, supercapacitors have become critical energy storage devices for new energy electric vehicles. In this paper, a ZnFe2O4@ZnCo2O4 core–shell cathode was prepared by a hydrothermal method followed by high-temperature annealing, and an AC@PANI composite anode was synthesized through in situ polymerization. The materials were characterized by SEM, TEM, XRD, XPS, nitrogen adsorption–desorption and electrochemical tests. The ZnFe2O4 rod-like core provides mechanical stability, whereas the ZnCo2O4 nanosheet shell increases the specific surface area and exposes more active sites. The cathode delivers 2133 F/g at 1 A/g with 94.4% retention after 10,000 cycles. The anode reaches 398 F/g at 1 A/g. The cathode delivers 2133 F/g at 1 A/g with 94.4% retention after 10,000 cycles. The anode reaches 398 F/g at 1 A/g. The assembled ZnFe2O4@ZnCo2O4//AC@PANI hybrid supercapacitor works in a wide voltage range of 0–1.6 V. It exhibits a specific capacitance of 157 F/g at 1 A/g and a high energy density of 54.7 Wh/kg at a power density of 1600 W/kg. The device retains 91.4% of its initial capacity after 10,000 charge–discharge cycles. This study offers a promising strategy for high-performance automotive supercapacitors.
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(This article belongs to the Special Issue Advancing Energy Storage Techniques: Chemistry, Materials and Devices)
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Open AccessArticle
Dynamic Analytical and Experimental Study of Wearable Thermoelectric Devices for Thermal Tactile Feedback
by
Zhijia Cai and Aibing Zhang
Micromachines 2026, 17(6), 694; https://doi.org/10.3390/mi17060694 (registering DOI) - 5 Jun 2026
Abstract
Thermal tactile perception plays a crucial role in enhancing realism and immersion in human–machine interaction, virtual/augmented reality, and wearable systems. By exploiting the thermoelectric effect to achieve precisely controllable heating and cooling, wearable thermoelectric devices (WTEDs) offer an effective approach for generating localized
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Thermal tactile perception plays a crucial role in enhancing realism and immersion in human–machine interaction, virtual/augmented reality, and wearable systems. By exploiting the thermoelectric effect to achieve precisely controllable heating and cooling, wearable thermoelectric devices (WTEDs) offer an effective approach for generating localized and programmable thermal sensations, which calls for a clear understanding of skin temperature regulation mechanisms. In this work, a dynamic thermal conduction model is developed for a skin–WTED integrated system incorporating a nickel foam-reinforced hydrogel heat sink, based on the dual-phase lag (DPL) bioheat conduction theory. The model accounts for blood perfusion and metabolic heat generation in skin tissue, as well as the Thomson effect within the thermoelectric legs and convective heat losses from their side surfaces. The theoretical predictions are validated through human skin temperature regulation experiments using a fabricated WTED, showing close agreement between experiments and simulations and confirming the model’s accuracy and reliability. Based on the validated model, the cooling current, filling factor, and thermoelectric leg height are optimized by minimizing the skin surface temperature. Furthermore, the model is applied to thermal tactile feedback studies, enabling the controlled reproduction of skin thermal sensations associated with common objects, including an iron block, a PMMA plate, and carbonated beverages packaged in aluminum cans and plastic bottles. Overall, this study provides a practical and predictive framework for understanding, optimizing, and applying WTEDs in thermal tactile feedback.
Full article
(This article belongs to the Section E:Engineering and Technology)
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Open AccessArticle
Real-Time Cutting Temperature Monitoring and Tool Wear Prediction with Integrated Thin-Film Thermocouples and Coupled Simulation
by
Yingyuan Luo, Fenghao Zuo, Binghai Lv, Xueliang Zhang and Xianfan Ge
Micromachines 2026, 17(6), 693; https://doi.org/10.3390/mi17060693 - 4 Jun 2026
Abstract
Accurate measurement of the temperature in the cutting zone is essential for closed-loop machining. However, it remains difficult due to the small size of the tool–chip contact area, its partial concealment by chips and the steep thermal gradients present. This study presents an
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Accurate measurement of the temperature in the cutting zone is essential for closed-loop machining. However, it remains difficult due to the small size of the tool–chip contact area, its partial concealment by chips and the steep thermal gradients present. This study presents an integrated framework that combines a thin-film thermocouple (TFTC) on the rake face of a polycrystalline cubic boron nitride (PCBN) tool with a thermo-mechanical wear-coupled simulation in order to monitor cutting temperature and predict tool wear. The three-dimensional finite-element turning model includes a moving heat source that represents plastic and frictional heat at the tool–chip interface, as well as an Archard-type wear law that is enhanced by a temperature correction factor. The TFTC is fabricated by magnetron sputtering NiCr and NiSi films onto an insulating layer, after which it is embedded in the tool as a minimally intrusive in situ sensor. Turning experiments on AISI 1045 steel were performed at spindle speeds of 1000–3000 rpm, feeds of 0.05–0.20 mm/rev and depths of cut ranging from 0.3 to 1.0 mm under dry, wet (emulsion) and cryogenic (liquid nitrogen) cooling conditions. Simulated temperature fields reveal strong localisation at the tool–chip contact and a nonlinear increase in peak rake-face temperature with spindle speed, which fits a quadratic regression with R2 = 0.99. The TFTC shows a response time of around 0.3 s with less than 5% overshoot, and its thermoelectric voltage is almost perfectly linear with temperature (R2 = 1), with a sensitivity of approximately 12 µV/°C. During cutting, TFTC readings agree with infrared measurements within ±3 °C and demonstrate improved robustness in occluded zones. The coupled wear model replicates the observed wear growth trend with the compact expression VB = 0.0001·t0.8. Sensitivity tests indicate that thermo-mechanical coupling increases wear rates compared to single-factor models, and that cooling reduces thermal loads by approximately 15% (wet) and 25% (cryogenic).
Full article
(This article belongs to the Special Issue Micro/Nanostructures in Sensors and Actuators, 2nd Edition)
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Open AccessArticle
High-Performance Asymmetric Supercapacitors Assembled from La-Doped ZnCo2O4/MnCo-LDH Nanoflower Positive Electrodes and Ti-Supported Sb-Doped SnO2 Negative Electrodes
by
Wei Xu, Changxu Qu, Mingzhao Xing, Jing Wang and Yanzhi Sun
Micromachines 2026, 17(6), 692; https://doi.org/10.3390/mi17060692 - 3 Jun 2026
Abstract
Transition-metal oxide/layered double hydroxide (LDH) electrodes often suffer from insufficient utilization of active sites, sluggish electron/ion transport, and limited cycling stability at high rates. Here, La-doped ZnCo2O4/MnCo-LDH nanoflowers serve as the positive electrode and Ti-supported Sb-doped SnO2 (Ti/Sb-SnO
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Transition-metal oxide/layered double hydroxide (LDH) electrodes often suffer from insufficient utilization of active sites, sluggish electron/ion transport, and limited cycling stability at high rates. Here, La-doped ZnCo2O4/MnCo-LDH nanoflowers serve as the positive electrode and Ti-supported Sb-doped SnO2 (Ti/Sb-SnO2) serves as the negative electrode for constructing an asymmetric supercapacitor. A stepwise hydrothermal route, La-doping regulation, and ethylenediamine-assisted morphology control transform stacked nanosheets into open porous nanoflowers with a specific surface area of 382.5 m2 g−1, thereby exposing more electroactive sites and shortening OH− diffusion pathways. La3+-induced lattice distortion and defect-related oxygen species further tune the electronic structure and improve interfacial charge-transfer kinetics. The optimized La-ZnCo2O4/MnCo-LDH electrode delivers 2130 F g−1 at 1 A g−1 and retains 1993 F g−1 after 10,000 cycles at 3 A g−1. The Ti/Sb-SnO2 negative electrode provides 673 F g−1 at 1 A g−1 and 302 F g−1 at 15 A g−1. The assembled device operates stably from 0 to 1.8 V in 2 M KOH and achieves 69 Wh kg−1 and 13,500 W kg−1.
Full article
(This article belongs to the Special Issue Advancing Energy Storage Techniques: Chemistry, Materials and Devices)
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Open AccessArticle
Optimization and Parallelization of Sorting by Interfacial Tension (SIFT) for High-Throughput Metabolic Cell Sorting
by
Aria Trivedi, Thomas Mathew, Matthew Shulman, Lakshmi Thangam, Pooja Dubey, Charlotte V. Cohen, Kelsey Voss and Paul Abbyad
Micromachines 2026, 17(6), 691; https://doi.org/10.3390/mi17060691 - 3 Jun 2026
Abstract
A systematic optimization of throughput and operational run time in Sorting by Interfacial Tension (SIFT) is presented. Reducing droplet size and enabling a broader distribution of droplet trajectories increased the number of droplets processed per sorting element, resulting in about a four-fold improvement
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A systematic optimization of throughput and operational run time in Sorting by Interfacial Tension (SIFT) is presented. Reducing droplet size and enabling a broader distribution of droplet trajectories increased the number of droplets processed per sorting element, resulting in about a four-fold improvement in throughput from 30 to 125 droplets per second. Throughput was further enhanced through device parallelization, as demonstrated by devices incorporating two and four independent sorting regions. These configurations distribute droplets evenly across sorting elements. The elements exhibited comparable pH sorting thresholds, indicating similar flow conditions and drag forces within each region. Among the designs evaluated, the two-element configuration provided the optimal balance of throughput, specificity, robustness, and simplicity. It achieved maximum throughputs of about 250 droplets per second. In many biological applications, only 1 in 20–30 droplets are occupied to minimize multiple-cell occupancy, resulting in an effective sorting rate of approximately 8 cells per second. Throughput and pH sorting thresholds were preserved for two hours of continuous cell sorting. The improved platform was applied to examine the relationship between cellular glycolysis and iron homeostasis at the single-cell level in activated Jurkat cells. It revealed a subpopulation of highly glycolytic cells with significantly elevated iron uptake, consistent with prior reports linking iron regulation and T cell metabolism. Collectively, these advances expand the scale, stability, and biological applicability of SIFT. These advances facilitate large-scale functional studies and the capture of rare, metabolically distinct, cell populations.
Full article
(This article belongs to the Special Issue Advanced Developments in Droplet Microfluidics)
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6–18 GHz High-Efficiency Power Amplifier MMIC Based on Broadband Impedance Matching
by
Shuai Liu, Xiaohua Ma, Yi Zhang, Zhaoke Bian and Chunliang Xu
Micromachines 2026, 17(6), 690; https://doi.org/10.3390/mi17060690 - 3 Jun 2026
Abstract
To meet the high standard requirements for broadband high-efficiency power amplifiers in modern communication technology, a 6–18 GHz high-efficiency monolithic microwave integrated circuit (MMIC) power amplifier was developed using a 0.25 μm gallium nitride high-electron mobility transistor (GaN HEMT) process. A multistage Chebyshev-filter-based
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To meet the high standard requirements for broadband high-efficiency power amplifiers in modern communication technology, a 6–18 GHz high-efficiency monolithic microwave integrated circuit (MMIC) power amplifier was developed using a 0.25 μm gallium nitride high-electron mobility transistor (GaN HEMT) process. A multistage Chebyshev-filter-based matching approach is utilized to provide the requisite bandwidth while concurrently managing second-harmonic terminations for enhanced PAE. In the final power stage, a multi-cell combining architecture is employed to achieve high saturated output power. The designed GaN amplifier achieves a saturated power of above 43.5 dBm and a PAE of over 30%. The area of the proposed GaN amplifier is 4 × 3.2 mm2. This chip, with its high efficiency and compact size, is promising for high-performance wideband systems.
Full article
(This article belongs to the Special Issue RF and Power Electronic Devices and Applications, 2nd Edition)
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Open AccessArticle
Research on Temperature Compensation Technology for a Flexible Capacitive Pressure Sensing System
by
Jianyi Zheng, Shuhan Chen and Zhicheng Xia
Micromachines 2026, 17(6), 689; https://doi.org/10.3390/mi17060689 - 2 Jun 2026
Abstract
Real-time pressure field measurement in aerospace vehicles is challenging because flexible sensor arrays must operate on curved surfaces under coupled thermal and pressure conditions. In this study, a temperature-compensated flexible capacitive pressure sensing system was developed for aerospace applications by integrating an 8
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Real-time pressure field measurement in aerospace vehicles is challenging because flexible sensor arrays must operate on curved surfaces under coupled thermal and pressure conditions. In this study, a temperature-compensated flexible capacitive pressure sensing system was developed for aerospace applications by integrating an 8 × 8 flexible sensor array, a multi-channel readout circuit based on time-division multiplexing and synchronous detection, and a Particle Swarm Optimization–Backpropagation (PSO-BP) neural network model. Calibration results showed high linearity, with a correlation coefficient of 0.9998 and a maximum relative error of 2.23%. Under coupled temperature–pressure conditions over 5–150 kPa and 10–110 °C, the average measurement error remained below 6%. Flight experiments further demonstrated valid in-flight data acquisition and trend-level pressure variations during key flight events, verifying the feasibility of the proposed approach for distributed aerospace pressure monitoring.
Full article
(This article belongs to the Special Issue Flexible and Wearable Sensors, 4th Edition)
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Open AccessArticle
Ultra-High Contact Electrified Current Generation and Chemical Sensing at IL-Based Immiscible Liquid–Liquid Interface
by
Yunfei Deng, Junyan Zhang, Hongmian Qi, Shaobin Wen, Chengfa Wang, Zhe Yu and Mengqi Li
Micromachines 2026, 17(6), 688; https://doi.org/10.3390/mi17060688 - 2 Jun 2026
Abstract
Though the charge transfer efficiency of a liquid–liquid (L-L) nanogenerator is much higher than that of the solid–liquid and solid–solid counterparts, there is still much room for improving the level of interfacial charge transfer. In this study, a power generation system was designed
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Though the charge transfer efficiency of a liquid–liquid (L-L) nanogenerator is much higher than that of the solid–liquid and solid–solid counterparts, there is still much room for improving the level of interfacial charge transfer. In this study, a power generation system was designed using an ionic liquid (IL)-based immiscible L-L interface via the contact/separation mode. The maximum output electric current reaches as high as about 8.12 μA by contacting a saturated NaCl droplet with an immiscible IL droplet. The magnitude of the generated electric current signals increases with an increase in the ionic concentration of the NaCl solution, the droplet contact area, and the liquid volume of IL. Moreover, the magnitude of the signals varies slightly when the pH value is under 12 and increases sharply in strong alkaline conditions. A maximum instantaneous power output of about 82 nW was obtained with a 100 kΩ resistor in series. The IL-based immiscible L-L interface configuration has been proven to be capable of sensing metal ions at an ultra-low concentration via the contact/separation mode.
Full article
(This article belongs to the Special Issue Electrokinetic and Electrochemical Phenomena in Microsystems)
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Open AccessReview
Progress in the Fabrication and Optimization of High-Energy Diamond X-Ray Refractive Lenses
by
Hao Huang, Kang Du, Wenbin He, Weiwei Zhang, Xiaohong Yang and Wuyi Ming
Micromachines 2026, 17(6), 687; https://doi.org/10.3390/mi17060687 - 1 Jun 2026
Abstract
The extreme thermal loads encountered in fourth-generation synchrotron radiation sources and X-ray free-electron lasers (XFEL) impose stringent requirements on X-ray optical components. Conventional materials such as beryllium and silicon increasingly exhibit limitations under high-energy conditions, including insufficient thermal conductivity, limited radiation stability, and
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The extreme thermal loads encountered in fourth-generation synchrotron radiation sources and X-ray free-electron lasers (XFEL) impose stringent requirements on X-ray optical components. Conventional materials such as beryllium and silicon increasingly exhibit limitations under high-energy conditions, including insufficient thermal conductivity, limited radiation stability, and significant absorption losses, rendering them inadequate for next-generation high-energy X-ray optics. In this context, single-crystal diamond, with its high thermal conductivity, low absorption coefficient, and excellent mechanical strength and radiation resistance, has emerged as a promising candidate for high-energy X-ray refractive optics. This review systematically summarizes recent advances in the fabrication and performance optimization of diamond X-ray refractive lenses for high-energy applications. Starting from the evolving demands of modern synchrotron radiation facilities and XFEL, the fundamental requirements for materials and structural design in high-energy X-ray optics are analyzed. Through comparisons with representative materials, the advantages of diamond in thermal management and transmission performance are highlighted. Major micro- and nanofabrication techniques, including femtosecond laser processing, focused ion beam milling, and plasma etching, are comprehensively reviewed, with emphasis on their respective characteristics in terms of processing efficiency, precision control, and damage introduction. The emerging trend of hybrid fabrication strategies is also discussed. Furthermore, the effects of surface roughness, subsurface damage, and crystal defects on wavefront quality and focusing performance are examined, along with corresponding post-processing and surface correction methods. Finally, current challenges related to large-size single-crystal growth, high-precision low-damage fabrication, and long-term operational stability are discussed, and future development directions for diamond-based X-ray refractive optical components are outlined.
Full article
(This article belongs to the Special Issue Micro/Nanomanufacturing and Cross-Scale Fabrication: Methods, Systems, and Applications)
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Open AccessArticle
Optimization and Predictive Modeling of SiC Wafer Dicing Using a Thin Diamond Grinding Wheel via RSM and NSGA-II
by
Jian Liu, Meiling Du, Jinzhong Wu, Sheng Gong, Penggen Ouyang, Shuai Huang and Fengjun Chen
Micromachines 2026, 17(6), 686; https://doi.org/10.3390/mi17060686 - 1 Jun 2026
Abstract
To investigate how the process parameters of ultra-thin diamond grinding wheel dicing affect the dicing quality of silicon carbide (SiC) wafers, single-factor experiments were designed. This study examined the influence of key process parameters, including spindle speed, feed rate, and first dicing depth,
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To investigate how the process parameters of ultra-thin diamond grinding wheel dicing affect the dicing quality of silicon carbide (SiC) wafers, single-factor experiments were designed. This study examined the influence of key process parameters, including spindle speed, feed rate, and first dicing depth, on the maximum chip width on the front side W1 and the maximum chip width on the back side W2, thereby determining their optimal parameter ranges. Subsequently, a quadratic polynomial prediction model was established using response surface analysis to analyze the interactive effects among the grinding wheel dicing process parameters. Finally, the prediction model was optimized using the genetic algorithm NSGA-II, and the optimal parameter combination for the two response variables was determined: a spindle speed of 31,960 r/min, a feed rate of 2.0019 mm/s, and a first dicing depth of 197.51 μm, yielding an average W1 of 4.8852 μm and W2 of 18.5360 μm. The relative errors between the predicted and average experimental values are 2.83% for W1 and 4.43% for W2. Both errors are below 5%, confirming the validity of the model. Therefore, the model serves as a practical reference for planning subsequent dicing processes using ultra-thin diamond grinding wheels.
Full article
(This article belongs to the Special Issue Ultra-Precision Micro Cutting and Micro Polishing)
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Open AccessArticle
Active-Learning-Guided Acoustic Metamaterial Resonators for Low-Frequency Noise Suppression and Piezoelectric Energy Harvesting
by
Syed Muhammad Anas Ibrahim and Jungyul Park
Micromachines 2026, 17(6), 685; https://doi.org/10.3390/mi17060685 - 31 May 2026
Abstract
Low-frequency traffic noise below 500 Hz is difficult to mitigate because its long wavelengths require impractically large conventional resonators. Here, we report an active-learning-guided inverse-design approach for scalable phononic-crystal-based acoustic metamaterial resonators that simultaneously suppress low-frequency noise transmission and harvest acoustic energy. The
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Low-frequency traffic noise below 500 Hz is difficult to mitigate because its long wavelengths require impractically large conventional resonators. Here, we report an active-learning-guided inverse-design approach for scalable phononic-crystal-based acoustic metamaterial resonators that simultaneously suppress low-frequency noise transmission and harvest acoustic energy. The approach combines Gaussian process regression surrogate modeling with genetic algorithm optimization to efficiently explore high-dimensional cavity geometries. By iteratively retraining the surrogate with FEM-validated designs, the active-learning process guides the search toward high-performance structures while reducing costly FEM evaluations compared with conventional GA optimization. After geometric scaling, the 2.5D prototype derived from the nine-point optimized cavity achieved a pressure amplification factor of approximately 20 near 490 Hz, while the revolved 3D cavity exhibited amplification exceeding 30 and a transmission loss of approximately 14 dB near the target frequency. Integrated with a mass-loaded five-PZT stack, the device generated 5.5 Vpp and 0.25 mW under 100 dB SPL, corresponding to a normalized power density of 0.58 μW Pa−2 cm−3. These results demonstrate a route toward multifunctional piezoelectric acoustic devices for noise mitigation, localized energy harvesting, and self-powered sensing.
Full article
(This article belongs to the Collection Piezoelectric Transducers: Materials, Devices and Applications)
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Open AccessArticle
Mechanics of Long-Shank 5 mm Neural Probe Insertion into the Rat Brain: Effects of Geometry and Vibration-Assisted Insertion
by
Mahasty Khajehzadeh, Christopher K. Nguyen, Mrigank Maharana, Shriya Peddapuram, Alexandra Joshi-Imre, Juan M. Pascual and Stuart F. Cogan
Micromachines 2026, 17(6), 684; https://doi.org/10.3390/mi17060684 - 31 May 2026
Abstract
Insertion of microelectrode arrays (MEAs) into brain tissue remains a mechanical challenge, especially for long, thin probes designed to access deep structures. This study investigates the mechanical properties of 5 mm long amorphous silicon carbide (a-SiC) probes with different geometries and the effect
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Insertion of microelectrode arrays (MEAs) into brain tissue remains a mechanical challenge, especially for long, thin probes designed to access deep structures. This study investigates the mechanical properties of 5 mm long amorphous silicon carbide (a-SiC) probes with different geometries and the effect of vibration-assisted insertion on penetration into rat brain. Methods: Two planar a-SiC probe designs were fabricated with identical lengths and thicknesses but differing width geometries: one with a uniform width (175 µm) and the other with a tapered shape (tapering from 175 to 75 µm). Critical buckling forces (FCs) were estimated by finite element modeling (FEM) and validated experimentally. Insertion mechanics were assessed in a brain mimic of 1.2% agarose gel at varying insertion speeds (20–1000 µm/s) and in vivo by implantation in rat cortex. Insertion metrics included penetration force (FP), cortical dimpling depth (Dd), maximum insertion force (Fmax), and success rate of insertion, all evaluated with and without vibrational assistance. Results: The tapered design exhibited lower penetration force and higher insertion success compared to the uniform-width probe, despite having a lower critical buckling force. An optimal insertion rate of 100 µm/s was identified, balancing insertion time with low Fmax and high insertion success across designs. Higher FP and Dd with a lower success rate were observed for uniform probes compared with tapered probes in rat brain. Vibration-assisted insertion was then investigated with tapered probes. Applying vibration significantly reduced FP, whereas Dd and Fmax remained unchanged. Notably, in 40% of actuated insertions in rat, no detectable FP peak was observed, suggesting unimpeded pial penetration. Conclusions: A tapered probe geometry and vibration-assisted insertion can reduce Fmax and FP while enhancing the insertion success rate for probe penetration in rat brain. These strategies are generally applicable to long-shank MEA insertions in brain and may inform design and insertion strategies.
Full article
(This article belongs to the Special Issue Neural Microelectrodes: Design, Integration, and Applications)
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Open AccessArticle
High-Update-Rate Frequency Readout of Sinusoidal Signals for Silicon Resonant Accelerometers Using Digital Closed-Loop Frequency Tracking
by
Xiangyu Zhang, Libin Huang, Song Xue and Zhenyu Sheng
Micromachines 2026, 17(6), 683; https://doi.org/10.3390/mi17060683 - 30 May 2026
Abstract
Silicon resonant accelerometers generate sinusoidal outputs with frequency shifts that carry acceleration information. At high update rates, conventional counting-based readout suffers from gate-boundary timing quantization. This work proposes a high-update-rate frequency readout method that reconstructs frequency from the continuous phase evolution of the
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Silicon resonant accelerometers generate sinusoidal outputs with frequency shifts that carry acceleration information. At high update rates, conventional counting-based readout suffers from gate-boundary timing quantization. This work proposes a high-update-rate frequency readout method that reconstructs frequency from the continuous phase evolution of the original sinusoidal resonant signal through quadrature demodulation, phase extraction, and phase difference rather than waveform reshaping and edge counting. To implement the proposed readout chain, an FLL–PLL cooperative loop was included to assist coarse acquisition and fine tracking on a Zynq-7020 platform. This study focuses on the readout principle, FPGA implementation, and prototype-level evaluation. At a 1 kHz update rate, the proposed method showed a lower theoretical quantization limit than the synchronous multi-cycle counting method. Under room-temperature conditions, after a 30 min startup, the proposed method reduced the standard deviation of the 1-second-averaged zero-bias output over 1800–5400 s from 4.1 μg to 2.4 μg and reduced the frequency-difference peak-to-peak value from 0.03743 Hz to 0.02410 Hz. These results support the feasibility and practical value of the proposed method for high-update-rate readout of sinusoidal resonant signals under the tested steady-state conditions.
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(This article belongs to the Special Issue Recent Advances in Silicon-Based MEMS Sensors and Actuators)
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Open AccessArticle
A Dual-FBG Sensor with Machine Learning for Microstrain–Temperature Decoupling Under Cyanoacrylate Bonding Toward Catheter Applications
by
Sung-Ho Yang, Cheng-Kai Yao, Amare Mulatie Dehnaw, Yong-Quan Zhuang and Peng-Chun Peng
Micromachines 2026, 17(6), 682; https://doi.org/10.3390/mi17060682 - 30 May 2026
Abstract
In cardiovascular interventional procedures, real-time, precise monitoring of minute strain and temperature fluctuations at the catheter tip is essential to improving both the safety and efficacy of these interventions. Fiber Bragg grating (FBG)-based sensors present a promising solution owing to their diminutive size
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In cardiovascular interventional procedures, real-time, precise monitoring of minute strain and temperature fluctuations at the catheter tip is essential to improving both the safety and efficacy of these interventions. Fiber Bragg grating (FBG)-based sensors present a promising solution owing to their diminutive size and immunity to electromagnetic interference; however, the inherent cross-sensitivity between strain and temperature remains a significant obstacle. This paper introduces a dual-FBG fiber optic sensing structure that leverages machine learning techniques. The system incorporates two FBGs: one set acts as the primary sensing element, positioned within a simulated catheter and affixed to the substrate under examination with cyanoacrylate adhesive to detect composite strain and temperature signals; the second set is spirally wound around the catheter surface to solely measure temperature, thus effectively isolating temperature interference. Additionally, a machine learning model is employed to learn the nonlinear mapping between the recorded FBG spectra and the actual strain and temperature parameters. Experimental validation was conducted within the physiologically relevant temperature range of 20 °C to 45 °C. The findings indicate that the proposed machine learning model can successfully decouple strain and temperature, achieving high-precision predictions even in situations where the sensing unit exhibits a slight nonlinear response due to adhesive bonding. This study substantiates the feasibility of utilizing machine learning-enhanced dual-FBG structures for multi-parameter sensing in complex environments. The proposed methodology presents a promising avenue for the development of next-generation smart optical fiber sensors intended for application in catheter systems.
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(This article belongs to the Special Issue MEMS and NEMS Sensors: Innovations, Applications, and Future Directions in Micro/Nano Technologies)
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Open AccessArticle
Research on an Efficient Barrier Adjustment Method for Bistable Vibration Energy Harvesters Based on a Rhombus Linkage Mechanism
by
Lulu Fu, Zhen Xiao, Tao Yu, Guansong Shan, Guanggui Cheng and Jie Song
Micromachines 2026, 17(6), 681; https://doi.org/10.3390/mi17060681 - 30 May 2026
Abstract
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Although bistable vibration energy harvesters offer promising broadband characteristics, their efficiency is often hindered by fixed potential barriers that confine the system to small-amplitude intra-well motion. The core innovation of this work is the proposal of a synchronous potential barrier regulation mechanism for
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Although bistable vibration energy harvesters offer promising broadband characteristics, their efficiency is often hindered by fixed potential barriers that confine the system to small-amplitude intra-well motion. The core innovation of this work is the proposal of a synchronous potential barrier regulation mechanism for multiple subsystems based on a rhombus linkage mechanism. This study introduces a novel multi-subsystem bistable vibration energy harvester (MBEH) integrated with a rhombus linkage mechanism to achieve tunable potential barriers. The mechanism facilitates the coupling of four bistable subsystems, where adjusting the magnet spacing of one subsystem allows for the synchronous regulation of magnetic gaps in others. This architecture ensures a continuous and precise optimization of the potential barrier. Consequently, this mechanism yields remarkable performance advancements, achieving highly efficient coupling among subsystems. Furthermore, potential barrier regulation efficiency is substantially increased, while operating bandwidths of subsystems are complementary and superimposed. Results from numerical investigations indicate that at an excitation acceleration of 0.6 g, MBEH outperforms conventional BEH with a 13.58 Hz increase in summed subsystem bandwidth and a 0.0223 μW gain in output power. The findings validate the efficacy of the proposed MBEH as a high-performance solution for robust broadband vibration energy harvesting.
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Open AccessArticle
Microstrip Antenna Bandwidth Optimization for RF Microsystems Using Swarm Intelligence and Reinforcement Learning
by
Shaolong Cao, Yu Shao, Jie Zhang, Yang Wang, Ju Tan, Kai Zhu and Lianghong Li
Micromachines 2026, 17(6), 680; https://doi.org/10.3390/mi17060680 - 30 May 2026
Abstract
As essential radiating elements in RF and microwave microsystems, microstrip antennas require sufficient bandwidth to ensure stable operation, integration flexibility, and overall microsystem performance. From a microsystem optimization perspective, this paper proposes a bandwidth extension method for microstrip antennas that combines swarm intelligence
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As essential radiating elements in RF and microwave microsystems, microstrip antennas require sufficient bandwidth to ensure stable operation, integration flexibility, and overall microsystem performance. From a microsystem optimization perspective, this paper proposes a bandwidth extension method for microstrip antennas that combines swarm intelligence and reinforcement learning. The proposed ICOA-TD3 framework is designed to enhance antenna bandwidth within target frequency bands and thus improve the performance robustness of compact RF microsystems. In the proposed method, an improved crayfish optimization algorithm (ICOA) is first used to explore the global design space and achieve global bandwidth enhancement, followed by the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm for local refinement and further exploitation of the antenna structure’s bandwidth potential. In Experiment 1, the impedance bandwidth ( ) is increased by up to 200%. In Experiment 2, the impedance bandwidth ( ) and axial-ratio (AR) bandwidth ( ) are improved by up to 27% and 250%, respectively. The results indicate that the proposed method is a feasible solution for bandwidth-oriented optimization of microstrip antennas and is promising for the intelligent design of high-performance RF microsystems.
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Open AccessArticle
Study and Optimization of a High-Performance SPR-PCF Temperature Sensor for Low-Temperature Monitoring Applications
by
Xinyuan Wang, Ke Jia, Zixi Fu, Yifan Feng, Jingheng Xiao, Yulin Wang and Wenjiang Ye
Micromachines 2026, 17(6), 679; https://doi.org/10.3390/mi17060679 - 30 May 2026
Abstract
To meet the demand for highly sensitive temperature sensing in low-temperature environments, a surface plasmon resonance photonic crystal fiber (SPR-PCF) sensor with a central air hole and a dual-layer air-hole arrangement is designed and optimized. In this work, these air-hole features are used
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To meet the demand for highly sensitive temperature sensing in low-temperature environments, a surface plasmon resonance photonic crystal fiber (SPR-PCF) sensor with a central air hole and a dual-layer air-hole arrangement is designed and optimized. In this work, these air-hole features are used for mode-field regulation in a low-temperature sensing structure based on surface plasmon resonance (SPR), together with a polished gold film and an ethanol/chloroform (1:1) temperature-sensitive medium. The finite element method (FEM) was employed to analyze the resonance behavior and thermal response, and key structural parameters, including gold-film thickness, air-hole sizes, and radial positions, were optimized through cumulative parametric scanning. The optimized sensor shows good temperature response from −25 °C to 40 °C, with a maximum sensitivity of 36 nm/°C, a full width at half-maximum (FWHM) of 18.57 nm, and a figure of merit (FOM) of 1.2923. It is promising for cold-chain monitoring, low-temperature storage and transportation, and low-temperature sensing.
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(This article belongs to the Section A:Physics)
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