Search Results (601)

This work presents a compact, self-powered wireless CO₂ sensing node for autonomous environmental monitoring. The system integrates a high-efficiency multijunction photovoltaic (PV) module, a 4000 F hybrid supercapacitor operating at 3.6–4.2 V, and a custom power management system in a LiPo-sized form factor. The PV module, composed of nine parallel triple-junction solar cells, achieves an average efficiency of 27% and delivers peak power at 4.26 V under 600 W/m² irradiance. The sensing unit includes miniaturized CO₂, humidity, and temperature sensors with LoRa-based wireless communication. The low-power NDIR CO₂ sensor provides a resolution of 15–20 ppm and a response time of ~45 s. Week-long tests demonstrated fully autonomous operation with reliable 5 min data transmission, capturing diurnal CO₂ variations associated with plant activity even under low irradiance. Energy storage occurs for irradiance levels ≥65 W/m², and long-term simulations confirm stable supercapacitor voltage over yearly cycles. This work demonstrates a compact multijunction solar–hybrid supercapacitor platform capable of sustaining WSN for long-term, maintenance-free CO₂ monitoring under real-world and low-irradiance conditions. Our results demonstrate that the sensing node can reliably monitor plant-driven CO₂ dynamics, clearly resolving the expected photosynthesis–respiration cycles and their dependence on incident solar radiation, while simultaneously sustaining its energy budget under highly challenging illumination and transmission conditions. Full article

Low-Temperature Co-Fired Ceramic (LTCC)-based mechanical sensors are inherently limited by the thickness and rigidity of multilayer ceramic stacks, which restrict miniaturization and mechanical compliance. To overcome these constraints, this work presents a hybrid LTCC/Kapton^® platform enabling high-sensitivity mechanical sensing through mechanically tunable RF passive components. The proposed approach integrates a flexible polyimide membrane, bonded onto an LTCC substrate at low temperatures using selectively electroplated indium pillars that simultaneously define the air gap and provide mechanical fixation. Inductance tuning is achieved via metal-shielding proximity effects, whereas capacitance tuning relies on force-controlled air-gap modulation in a metal–insulator–metal configuration. The fabrication process ensures precise gap control, high compliance, and structural robustness without requiring deformable ceramic membranes. Experimental characterization, including three-dimensional surface profiling and impedance measurements, demonstrates a 48% inductance tuning range with a sensitivity of 0.715 nH/mN and a 36% capacitance tuning range with a sensitivity of 47.3 fF/mN at 1 MHz. The proposed hybrid platform provides a compact and scalable solution for high-sensitivity sensors and mechanically reconfigurable RF components suitable for harsh-environment and adaptive electronics applications. Full article

In recent years, the trend toward spacecraft miniaturization has led to the widespread adoption of micro- and nanosatellites, driven by their reduced development costs and simplified launch logistics. Operating these platforms in coordinated fleets, or swarms, represents a promising approach to overcoming the inherent limitations of individual spacecraft by distributing sensing and processing capabilities across multiple units. For systems of this scale, decentralized guidance and control architectures based on so-called behavioral strategies offer an attractive solution. These approaches are inspired by biological swarms, which exhibit remarkable robustness and adaptability through simple local interactions, minimal information exchange, and the absence of centralized supervision, but their application to space scenarios is limited, if not negligible. This work investigates the feasibility of autonomous swarm maintenance subject to orbital forces, under the stringent actuation, sensing, and computational constraints typical of nanosatellite platforms. Each spacecraft is assumed to carry a single monocular camera aligned with the along-track direction. The proposed behavioral control framework enables decentralized formation keeping without ground intervention or centralized coordination. Since control actions rely on the relative motion of neighboring satellites, a lightweight relative navigation capability is required. The results indicate that complex vision pipelines can be replaced by simple blob-based image processing, although a (rough) reconstruction of elative parameters remains essential to avoid unnecessary control effort arising from suboptimal guidance decisions. Full article

Smart healthcare is rapidly emerging as a transformative paradigm, enabling simultaneous health monitoring, therapeutic intervention, and early prediction of disease onset. In this context, electrochemical monitoring systems have attracted growing interest due to their cost-effectiveness, ease of operation, miniaturization and compatibility with wearable platforms. Accordingly, conductive hydrogel-based electrochemical (bio)sensors have gained significant attention for health monitoring owing to their soft mechanical properties, high water content, excellent biocompatibility, and ability to form intimate, conformal interfaces with biological tissues. Their three-dimensional polymeric networks facilitate efficient ion transport and mechanical flexibility, making them particularly suitable for wearable and noninvasive sensing and monitoring applications. However, the intrinsically limited conductivity and catalytic activity of pristine hydrogels often constrain their electrochemical performance. To overcome these limitations, functional nanomaterials such as metal–organic frameworks (MOFs) and MXene (MX) nanosheets have been increasingly integrated into hydrogel matrices to enhance conductivity and electrochemical activity. This review provides a comprehensive and critical comparison of recent advances in MOF- and MX-integrated conductive hydrogels for electrochemical health monitoring. In addition to material design strategies and sensing performance, emerging trends in data-driven sensing aimed at improving signal interpretation and multi-analyte discrimination are systematically discussed. Key challenges related to long-term stability, biocompatibility, scalability, and intelligent system integration are critically assessed, and the future potential of these platforms within closed-loop architectures is highlighted, paving the way for next-generation conductive hydrogel-based electrochemical sensors in smart healthcare applications. Full article

Electrochemical biosensors represent mature platforms for point-of-need analysis due to their high sensitivity, intrinsic selectivity, low cost, and facile miniaturization. In the last decade, nanomaterials have become integral to advanced biosensor architectures, acting as high-surface-area supports, electron-transfer mediators, and signal-amplifying elements. This review critically examines the most represented nanomaterial classes in mature electrochemical biosensors—carbon nanostructures, gold nanoparticles, and iron-based magnetic nanoparticles—highlighting how morphology, electronic structure, and surface chemistry influence key performance metrics such as limit of detection, linear range, and assay time. Despite a strong technology push and numerous proof-of-concept demonstrations, the translation of nanomaterial-enabled electrochemical biosensors into commercial devices remains limited. This gap arises from the intrinsic physicochemical complexity of nanomaterials, which hampers standardization, reproducibility, and long-term safety assessment. Accordingly, this review integrates performance analysis with a systematic overview of the European regulatory framework, including the Medical Device Regulation (MDR) (EU) 2017/745, the In Vitro Diagnostic Regulation (IVR) (EU) 2017/746, EFSA guidance for food and water applications, and relevant ISO standards, outlining key translational bottlenecks and design principles for deployable biosensing technologies. Full article

Dynamic monitoring of hemostatic equilibrium is indispensable for clinical safety in high-risk scenarios, while current clinical methods are limited by sample volume, detection speed, and physiological relevance. These shortcomings underscore the demand for novel sensing platforms. Optical biosensors, leveraging label-free detection, rapid response, and multi-level characterization, could serve as a transformative solution for decentralized and point-of-care monitoring. This review systematically summarizes advances in optical coagulation testing, encompassing light transmission aggregometry, laser speckle rheology, optical coherence tomography/elastography, optic–acoustic coupled methods, and fluorescence biosensing. These technologies complementarily capture structural and mechanical and some molecular and cellular dynamics of coagulation, bridging gaps in traditional assays. Despite promising preclinical and clinical correlations, translation barriers persist in lack of standardization of metrics, interference mitigation, and multi-center validation in diverse patient cohorts. Future development of optical biosensing platforms for coagulation testing should focus on modular integration, AI-aided interference correction, and microfluidic miniaturization to realize actionable, real-time coagulation assessment. Optical biosensors hold unparalleled potential to transform hemostatic monitoring from static endpoint testing to dynamic, interpretable evaluation, guiding personalized clinical decisions. Full article

The rapid and accurate detection of pathogenic bacteria and viruses is essential for controlling infectious disease outbreaks and ensuring food safety. Conventional detection methods such as microbial culture, immunoassays, and polymerase chain reaction (PCR), although effective, often suffer from drawbacks including time-consuming procedures, complex operations, and limited multiplexing capabilities. In recent years, electrochemical aptasensors have emerged as a promising alternative for rapid detection of pathogenic bacteria, viruses, and by-products (toxins) due to their high sensitivity, excellent specificity, low cost, and potential for miniaturization. Aptamers can be applied as biorecognition elements of the biosensor, remarkably offering advantages such as high binding affinity, thermal stability, and ease of chemical synthesis. Meanwhile, nanomaterials which provide large surface area, superior conductivity, and modifiable surfaces are widely employed in signal amplification and sensor platform construction. This review discusses the cutting-edge innovations in electrochemical aptasensors in recent years that utilize various types of nanomaterials to accurately identify and quantify diverse types of pathogens and toxins. This review focuses on nanomaterials such as metal nanostructures, carbon nanomaterials, metal, metal oxides, and carbon nanocomposites that can synergistically enhance detection sensitivity, specificity, and operational stability. This review also highlights the promising practical application of the proposed electrochemical aptasensors in clinical diagnostics, environmental monitoring, and food safety. Full article

To meet the miniaturization and lightweight requirements of inter-satellite laser communication, this study investigates the servo control system of a silicon-based optical phased array (OPA). Based on the far-field radiation model for beam steering of the silicon-based OPA, combined with thermo-optic phase modulation technology and time domain response, the transfer function of the silicon-based OPA is established. To address noise and disturbances encountered during actual tracking, a silicon-based OPA beam tracking method for satellite platform vibration is proposed. The control algorithm employs a Kalman filter-based Model Predictive Control (KF-MPC) strategy. The advantages of the designed control algorithm were verified through simulations and experiments. Step response simulation results show that compared with the traditional PID control algorithm, the proposed algorithm reduces overshoot by 15.1% and shortens the response time by 76.4%. Sinusoidal tracking simulation results indicate a 27.15% improvement in tracking accuracy over the traditional PID algorithm. Experimental results demonstrate that the tracking accuracy of the servo control system with the proposed algorithm is 155.45 μrad, while that using the PID algorithm is 210.97 μrad, representing a 26.31% improvement in tracking accuracy. This research provides a valuable reference for the application of silicon-based OPA in inter-satellite laser communication. Full article

Traditional involute gear pumps find it difficult to meet the requirements of miniaturization and high performance because of the undercutting, trapped oil, and flow pulsation. To eliminate the phenomenon of trapped oil and reduce flow pulsation in the miniature gear pump, a novel miniature double-circular-arc line gear (MDLG) and its manufacturing method are proposed. Firstly, based on the spatial curve meshing theory, the tooth flank equation of the MDLG is established, and the design method of the MDLG hob is presented. Then, the instantaneous flow rate of the MDLG pump is analyzed by using the swept-area method. Subsequently, a hobbing machining model is built on the VERICUT virtual simulation platform, and machining experiments are conducted on a hobbing machine. Furthermore, the manufactured MDLGs are inspected at a gear measuring center. Finally, an MDLG pump prototype is developed and machined. The measurement results show that the total cumulative pitch deviations of the machined MDLGs are controlled within 32.1 μm, achieving the ISO 8 accuracy grade. The theoretical calculations and experimental results in this article verify the feasibility of the design and processing of MDLG pumps, providing a reference for the development of high-performance miniature gear pumps. Full article

Microextraction Technologies (METs) have emerged as pivotal exposomic sensors for the on-site monitoring of Volatile Organic Compounds (VOCs) in ambient air. By integrating sampling and sample preparation into a single step, METs provide solvent-free, miniaturized, and field-deployable solutions that align with the principles of green analytical chemistry. This review critically examines fourteen commercially available METs, selected for their demonstrated analytical performance, commercial accessibility, and validation in real-world environments. These devices represent the current state of practice in exposomics, enabling both short-term hotspot detection and long-term exposure assessment. Particular attention is given to their compatibility with transportable and portable detection platforms, including vehicle-mounted and hand-held gas chromatography/mass spectrometry systems, where METs function as front-end concentrators that enhance sensitivity and spatial resolution. This review further discusses emerging applications in wearable formats and unmanned aerial vehicles, underscoring the role of METs in bridging laboratory-grade precision with field-based exposome research. By situating METs within the broader exposomic workflow of sampling, detection, and interpretation, this work identifies current technological gaps and outlines priorities for advancing robust, scalable, and environmentally sustainable exposure assessment strategies. Full article

Microfluidic chip technologies, also known as lab-on-a-chip systems, have profoundly transformed laboratory medicine by enabling the miniaturization, automation, and rapid processing of complex diagnostic assays using minimal sample volumes. Recent advances in chip design, fabrication methods—including 3D printing, modular and flexible substrates—and biosensor integration have significantly enhanced the performance, sensitivity, and clinical applicability of these devices. Integration of advanced biosensors allows for real-time detection of circulating tumor cells, nucleic acids, and exosomes, supporting innovative applications in cancer diagnostics, infectious disease detection, point-of-care testing (POCT), personalized medicine, and therapeutic monitoring. Notably, the convergence of microfluidics with artificial intelligence (AI) and machine learning has amplified device automation, reliability, and analytical power, resulting in “smart” diagnostic platforms capable of self-optimization, automated analysis, and clinical decision support. Emerging applications in fields such as neuroscience diagnostics and microbiome profiling further highlight the broad potential of microfluidic technology. Here, we present findings from a comprehensive review of recent innovations in microfluidic chip design and fabrication, advances in biosensor and AI integration, and their clinical applications in laboratory medicine. We also discuss current challenges in manufacturing, clinical validation, and system integration, as well as future directions for translating next-generation microfluidic technologies into routine clinical and public health practice. Full article

Advances in artificial intelligence (AI), soft robotics, and miniaturized imaging technologies have accelerated the development of endorobotic platforms that aim to enhance detection accuracy and improve patient experience. In this narrative review, we synthesize evidence on AI-assisted detection and characterization systems (CADe/CADx), robotic locomotion mechanisms, adhesion strategies, imaging modalities, and material and power constraints relating to next-generation CRC screening technologies. Reported performance metrics are interpreted within their original methodological contexts, acknowledging the heterogeneity of datasets, limited representation of diverse populations, underreporting of negative findings, and scarcity of large, real-world comparative trials. We introduce a conceptual translational framework that links engineering design principles with validation needs across in silico, in vitro, preclinical, and clinical stages, and we outline safety considerations, workflow integration challenges, and sterility requirements that influence real-world deployability. Regulatory alignment is discussed using the U.S. FDA Total Product Life Cycle (TPLC) and Good Machine Learning Practice (GMLP) frameworks to highlight expectations for data quality, model robustness, device–software interoperability, and post-market monitoring. Collectively, the evidence demonstrates promising technological innovation but also highlights substantial gaps that must be addressed before AI-enabled endorobotic systems can be safely and effectively integrated into routine CRC screening. Continued interdisciplinary work, supported by rigorous validation and transparent reporting, will be essential to advance these technologies toward meaningful clinical impact. Full article

Current liquid-phase resonant biosensors, such as Quartz Crystal Microbalance, Surface Acoustic Wave, or Surface Plasmon Resonance, typically rely on specialized piezoelectric substrates or complex optical setups. These requirements often necessitate cleanroom fabrication, thereby limiting cost-effective scalability. This study presents a high-integration sensing platform based on standard Printed Circuit Board (PCB) technology, incorporating an embedded inductor within a fluidic system for real-time monitoring. This design leverages industrial manufacturing standards to achieve a compact, low-cost, and scalable architecture. Detection is governed by shifts in the resonance frequency of an LC tank circuit; specifically, increases in bulk ionic strength induce a frequency decrease, whereas biomolecular adsorption at the sensor surface leads to a frequency increase. This phenomenon can be explained by the modulation of the inter-turn capacitance, which is modeled as a combination of capacitive elements accounting for contributions from the bulk electrolyte and the surface-bound dielectric layer. Such divergent responses provide an intrinsic self-discriminating capability, allowing for the analytical differentiation between surface interactions and bulk effects. To the best of our knowledge, this is the first demonstration of an inductor-based resonant sensor fully embedded in a PCB fluidic architecture for continuous liquid-phase analyte monitoring. Validated through a protein-antibody model (Bovine Serum Albumin-anti-Bovine Serum Albumin), the sensor demonstrated a limit of detection of 1.7 ppm (0.026 mM) and a linear dynamic range of 31–211 ppm (0.47–3.2 mM). These performance metrics, combined with a reproducibility of 4 ± 3%, indicate that the platform meets the requirements for robust analytical applications. Its inherent simplicity and potential for miniaturization position this technology as a viable candidate for point-of-care diagnostics in diverse environments. Full article

Dopamine (DA) is a critical catecholaminergic neurotransmitter that facilitates signal transduction across synaptic junctions and modulates essential neurophysiological processes, including motor coordination, motivational drive, and reward-motivated behaviors. The fabrication of cost-effective, miniaturized, and high-fidelity analytical platforms is imperative for real-time DA monitoring. Due to its inherent electrochemical activity, carbon-based amperometric sensors constitute the primary modality for DA quantification. In this study, graphite, multi-walled carbon nanotubes (MWCNTs), and graphene were immobilized within an ethyl 2-cyanoacrylate (ECA) polymer matrix. ECA was selected for its rapid polymerization kinetics and established biocompatibility in electrochemical frameworks. All fabricated composites demonstrated robust electrocatalytic activity toward DA; however, MWCNT- and graphene-based sensors exhibited superior analytical performance, characterized by highly competitive limits of detection (LOD) and quantification (LOQ). Specifically, MWCNT-modified electrodes achieved an interesting LOD of 0.030 ± 0.001 µM and an LOQ of 0.101 ± 0.008 µM. Discrepancies in baseline current amplitudes suggest that the spatial orientation of carbonaceous nanomaterials within the cyanoacrylate matrix significantly influences the electrochemical surface area and resulting baseline characteristics. The impact of interfering species commonly found in biological environments on the sensors’ response was systematically evaluated. The best-performing sensor, the graphene-based one, was used to measure the DA intracellular content of PC12 cells. Full article

Compact antennas with ultra-wideband operation and stable radiation are essential for portable and airborne ground-penetrating radar (GPR), yet miniaturization in the sub 3 GHz region is strongly constrained by the wavelength-driven aperture requirement and often leads to impedance discontinuity and radiation instability. This paper presents a compact aperture-slot antipodal Vivaldi antenna (AS-AVA) designed under a radiation stability-driven co-design strategy, where the miniaturization features are organized along the energy propagation path from the feed to the flared aperture. The proposed structure combines (i) aperture-slot current-path engineering with controlled meandering to extend the low-frequency edge, (ii) four tilted rectangular slots near the aperture to restrain excessive edge currents and suppress sidelobes, and (iii) back-loaded parasitic patches for coupling-based impedance refinement to eliminate residual mismatch pockets. A fabricated prototype on FR-4 (thickness 1.93 mm) occupies $111.15\times 156.82$ mm² and achieves a measured $S_{11}$ below $-10$ dB from 0.63 to 2.03 GHz (fractional bandwidth 105.26%). The measured realized gain increases from 2.1 to 7.5 dBi across the operating band, with stable far-field radiation patterns; the group delay measured over 0.6–2.1 GHz remains within 4–8 ns, indicating good time-domain fidelity for stepped-frequency continuous-wave (SFCW) operation. Finally, the antenna pair is integrated into an SFCW-GPR testbed and validated in sandbox and outdoor experiments, where buried metallic targets and a subgrade void produce clear B-scan signatures after standard processing. These results confirm that the proposed AS-AVA provides a practical trade-off among miniaturization, broadband matching, and radiation robustness for compact sub 3 GHz GPR platforms. Full article