Observation of localized magnetic plasmon skyrmions

Optical skyrmions have recently been constructed by tailoring vectorial near-field distributions through the interference of multiple surface plasmon polaritons, offering promising features for advanced information processing, transport and storage. Here, we provide experimental demonstration of electromagnetic skyrmions based on magnetic localized spoof plasmons (LSP) showing large topological robustness against continuous deformations, without stringent external interference conditions. By directly measuring the spatial profile of all three vectorial magnetic fields, we reveal multiple π-twist target skyrmion configurations mapped to multi-resonant near-equidistant LSP eigenmodes. The real-space skyrmion topology is robust against deformations of the meta-structure, demonstrating flexible skyrmionic textures for arbitrary shapes. The observed magnetic LSP skyrmions pave the way to ultra-compact and robust plasmonic devices, such as flexible sensors, wearable electronics and ultra-compact antennas.

Self-Powered Flexible Sensing System Based on Super-Tough, High Ionic Conductivity and Rapid Self-Recovery Fully Physically Crosslinked Double Network Hydrogel

At present, hydrogel flexible sensors have attracted wide attention in the field of wearable electronic devices. However, hydrogel flexible sensors need external solid state power supply to output stable signals....

Self-healing, Mechanically Robust, and 3D Printable Ionogel for Highly Sensitive and Long-Term Reliable Ionotronics

Flexible sensors which can transduce various stimuli (e.g., strain, pressure, temperature) into electrical signals are highly in demand due to the development of human-machine interaction. However, it is still a...

Recent Advances in Self-Powered Piezoelectric and Triboelectric Sensors: From Material and Structure Design to Frontier Applications of Artificial Intelligence

The development of artificial intelligence and the Internet of things has motivated extensive research on self-powered flexible sensors. The conventional sensor must be powered by a battery device, while innovative self-powered sensors can provide power for the sensing device. Self-powered flexible sensors can have higher mobility, wider distribution, and even wireless operation, while solving the problem of the limited life of the battery so that it can be continuously operated and widely utilized. In recent years, the studies on piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs) have mainly concentrated on self-powered flexible sensors. Self-powered flexible sensors based on PENGs and TENGs have been reported as sensing devices in many application fields, such as human health monitoring, environmental monitoring, wearable devices, electronic skin, human–machine interfaces, robots, and intelligent transportation and cities. This review summarizes the development process of the sensor in terms of material design and structural optimization, as well as introduces its frontier applications in related fields. We also look forward to the development prospects and future of self-powered flexible sensors.

Highly stretchable conductive fabric using knitted cotton/lycra treated with polypyrrole/silver NPs composites post-treated with PEDOT:PSS

Flexible sensors and wearable electronics have become important in recent years. A good conductive and flexible textile is needed to develop a commercial wearable device. Conductive polymers have generally been used with limitation in reducing the surface resistance to a certain amount. In this research, a method for fabricating a stretchable highly conductive cotton/lycra knitted fabric is introduced by treating the fabric with polypyrrole (PPy), silver nanoparticles (SNPs) composites, and post-treating with poly (3,4-ethylenedioxythiophene) poly (styrenesulfonate) (PEDOT:PSS). Polypyrrole and SNPs were in situ fabricated on the cotton/lycra fabric by consecutive redox reaction of silver nitrate and pyrrole and finally covered by PEDOT:PSS solution through dip-coating. The coated textile was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), X-ray mapping, and energy dispersive X-ray spectroscopy (EDX). Fourier transform infrared spectroscopy confirmed PPy-SNPs (P-S) composites on the fabric surface. Fourier transform infrared spectroscopy results, X-ray mapping, EDAX, and XRD analysis also confirmed the P-S composites and PEDOT:PSS polymeric layer on the fabric. Morphological observation showed a layer of PEDOT:PSS on the P-S caused the higher connection of coating on textiles which resulted in the higher electrical conductivity (43 s/m). Also morphological observations showed penetration of the silver particles inside fibers which represented improving in attachment and stability of the coating on the fibers. Further, the electrical conductivity of PPy-SNPs-PEDOT:PSS coated textile increased under the tension. Hence, the stretchable and highly conductive knitted cotton/lycra fabric has potentiality to be used for fabricating the flexible sensors or wearable electronics.

Design and Manufacture of Data Gloves for Rehabilitation Training and Gesture Recognition Based on Flexible Sensors

This work takes the production and usage scenarios of the data glove as the research object and studies the method of applying the flexible sensor to the data glove. Many studies are also devoted to exploring the transplantation of flexible sensors to data gloves. However, this type of research still lacks the display of specific application scenarios such as gesture recognition or hand rehabilitation training. A small amount of experimental data and theoretical analysis are difficult to promote the development of flexible sensors and flexible data gloves design schemes. Therefore, this study uses the self-made flexible sensor of the research group as the core sensing unit to produce a flexible data glove to monitor the bending changes of the knuckles and then use it for simple gesture recognition and rehabilitation training.