Wearable antennas have recently garnered significant attention due to their attractive properties and potential for creating lightweight, compact, low-cost, and multifunctional wireless communication systems. With the breakthrough progress in nanomaterial research, the use of lightweight materials has paved the way for the widespread application of wearable antennas. Compared with traditional metallic materials like copper, aluminum, and nickel, nanoscale entities including zero-dimensional (0-D) nanoparticles, one-dimensional (1-D) nanofibers or nanotubes, and two-dimensional (2-D) nanosheets exhibit superior physical, electrochemical, and performance characteristics. These properties significantly enhance the potential for constructing durable electronic composites. Furthermore, the antenna exhibits compact size and high deformation stability, accompanied by greater portability and wear resistance, owing to the high surface-to-volume ratio and flexibility of nanomaterials. This paper systematically discusses the latest advancements in wearable antennas based on 0-D, 1-D, and 2-D nanomaterials, providing a comprehensive overview of their development and future prospects in the field.

Synthetic route and properties of flower-like NiO used as a cathodic catalyst in rechargeable Li–O₂batteries.

Sweat is an accessible biofluid that provides useful physiological information about the body’s biomolecular state and systemic health. Wearable sensors possess various advantageous features, such as lightweight design, wireless connectivity, and compatibility with human skin, that make them suitable for continuous monitoring. Wearable electrochemical sweat sensors can diagnose diseases and monitor health conditions by detecting biomedical signal changes in sweat. This paper discusses the state-of-the-art research in the field of wearable sweat sensors and the materials used in their construction. It covers biomarkers present in sweat, sensing modalities, techniques for sweat collection, and ways to power these sensors. Innovative materials are categorized into three subcategories: sweat collection, sweat detection, and self-powering. These include substrates for sensor fabrication, analyte detection electrodes, absorbent patches, microfluidic devices, and self-powered devices. This paper concludes by forecasting future research trends and prospects in material-based wearable non-invasive sweat sensors.

In order to solve the springback problem in sheet metal forming, the trial and error method is a widely used method in the factory, which is time-consuming and costly for its non-direction and non-quantitative. Finite element simulation is an effective method to predict the springback of complex shape parts, but its precision is sensitive to the simulation model, particularly material model and boundary conditions. In this paper, the simple iterative method is introduced to establish the iterative compensation algorithm, and the convergence criterion of iterative parameters is put forward. In addition, the new algorithm is applied to the V-free bending and stretch-bending processes, and the convergence of curvature and bending angle is proved theoretically and verified experimentally. At the same time, the iterative compensation experiments for plane bending show that, the new method can predict the next compensation value based on the springback of each test, so that the target bending angle with the error of less than ± 0.1% and the target curvature with the error of less than 0.5% are obtained after 2‒3 iterations. This research proposes a new iterative compensation algorithm to predict springback in sheet metal forming process, where each compensation value depends only on the iteration parameter difference before and after springback for the same forming process of same material.

Isothermal hot compression tests of TC4–DT titanium alloy were performed under temperatures of 1203–1293 K and strain rates of 0.001–10 s⁻¹. The purpose of this study is to develop a new high-precision modified constitutive model that can describe the deformation behavior of TC4–DT titanium alloy. Both the modified strain-compensated Arrhenius-type equation and the modified Hensel–Spittel equation were established by revising the strain rate. The parameters in the above two modified constitutive equation were solved by combining regression analysis with iterative methods, which was used instead on the traditional linear regression methods. In addition, both the original strain-compensated Arrhenius-type equation and Hensel–Spittel equation were established to compare with the new modified constitutive equations. A comparison of the predicted values based on the four constitutive equations was performed via relative error, average absolute relative error (AARE) and the correlation coefficient (R). These results show the modified Arrhenius-type equation and the modified Hensel–Spittel equation is more accurate and efficient with a similar prediction accuracy. The AARE-value of the two modified constitutive equation is relatively low under various strain rates and their fluctuation is small as the strain rate changes.