The miniaturization and low power consumption characteristics of RF MEMS (Radio Frequency Microelectromechanical System) switches provide new possibilities for the development of microsatellites and nanosatellites, which will play an increasingly important role in future space missions. This paper provides a comprehensive review of RF MEMS switches in satellite communication, detailing their working mechanisms, performance optimization strategies, and applications in reconfigurable antennas. It explores various driving mechanisms (electrostatic, piezoelectric, electromagnetic, thermoelectric) and contact mechanisms (capacitive, ohmic), highlighting their advantages, challenges, and advancements. The paper emphasizes strategies to enhance switch reliability and RF performance, including minimizing the impact of shocks, reducing driving voltage, improving contacts, and appropriate packaging. Finally, it discusses the enormous potential of RF MEMS switches in future satellite communications, addressing their technical advantages, challenges, and the necessity for further research to optimize design and manufacturing for broader applications and increased efficiency in space missions. The research findings of this review can serve as a reference for further design and improvement of RF MEMS switches, which are expected to play a more important role in future aerospace communication systems.

In recent years, advancements in the Internet of Things (IoT), manufacturing processes, and material synthesis technologies have positioned flexible sensors as critical components in wearable devices. These developments are propelling wearable technologies based on flexible sensors towards higher intelligence, convenience, superior performance, and biocompatibility. Recently, two-dimensional nanomaterials known as MXenes have garnered extensive attention due to their excellent mechanical properties, outstanding electrical conductivity, large specific surface area, and abundant surface functional groups. These notable attributes confer significant potential on MXenes for applications in strain sensing, pressure measurement, gas detection, etc. Furthermore, polymer substrates such as polydimethylsiloxane (PDMS), polyurethane (PU), and thermoplastic polyurethane (TPU) are extensively utilized as support materials for MXene and its composites due to their light weight, flexibility, and ease of processing, thereby enhancing the overall performance and wearability of the sensors. This paper reviews the latest advancements in MXene and its composites within the domains of strain sensors, pressure sensors, and gas sensors. We present numerous recent case studies of MXene composite material-based wearable sensors and discuss the optimization of materials and structures for MXene composite material-based wearable sensors, offering strategies and methods to enhance the development of MXene composite material-based wearable sensors. Finally, we summarize the current progress of MXene wearable sensors and project future trends and analyses.

Underwater target detection is a critical task in various applications, including environmental monitoring, underwater exploration, and marine resource management. As the demand for underwater observation and exploitation continues to grow, there is a greater need for reliable and efficient methods of detecting underwater targets. However, the unique underwater environment often leads to significant degradation of the image quality, which results in reduced detection accuracy. This paper proposes an improved YOLOv5 underwater-target-detection network to enhance accuracy and reduce missed detection. First, we added the global attention mechanism (GAM) to the backbone network, which could retain the channel and spatial information to a greater extent and strengthen cross-dimensional interaction so as to improve the ability of the backbone network to extract features. Then, we introduced the fusion block based on DAMO-YOLO for the neck, which enhanced the system’s ability to extract features at different scales. Finally, we used the SIoU loss to measure the degree of matching between the target box and the regression box, which accelerated the convergence and improved the accuracy. The results obtained from experiments on the URPC2019 dataset revealed that our model achieved an mAP@0.5 score of 80.2%, representing a 1.8% and 2.3% increase in performance compared to YOLOv7 and YOLOv8, respectively, which means our method achieved state-of-the-art (SOTA) performance. Moreover, additional evaluations on the MS COCO dataset indicated that our model’s mAP@0.5:0.95 reached 51.0%, surpassing advanced methods such as ViDT and RF-Next, demonstrating the versatility of our enhanced model architecture.

Nanogenerators possess the capability to harvest faint energy from the environment. Among them, thermoelectric (TE), triboelectric, piezoelectric (PE), and moisture-enabled nanogenerators represent promising approaches to micro–nano energy collection. These nanogenerators have seen considerable progress in material optimization and structural design. Printing technology has facilitated the large-scale manufacturing of nanogenerators. Although inks can be compatible with most traditional functional materials, this inevitably leads to a decrease in the electrical performance of the materials, necessitating control over the rheological properties of the inks. Furthermore, printing technology offers increased structural design flexibility. This review provides a comprehensive framework for ink-based nanogenerators, encompassing ink material optimization and device structural design, including improvements in ink performance, control of rheological properties, and efficient energy harvesting structures. Additionally, it highlights ink-based nanogenerators that incorporate textile technology and hybrid energy technologies, reviewing their latest advancements in energy collection and self-powered sensing. The discussion also addresses the main challenges faced and future directions for development.