Liquid Metal-Tailored PEDOT:PSS for Noncontact Flexible Electronics with High Spatial Resolution.

ACS nano(2022)

引用 9|浏览15
暂无评分
摘要
Electric field-based noncontact flexible electronics (EF-NFEs) allow people to communicate with intelligent devices through noncontact human-machine interactions, but current EF-NFEs with limited detections (usually <20 cm) distance often lack a high spatial resolution. Here, we report a versatile material for preparing EF-NFE devices with a high spatial resolution to realize everyday human activity detection. Eutectic gallium-indium alloy (EGaIn) was introduced into poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) chains to fabricate this material, named Ga-PP. The introduction of EGaIn successfully regulates the intra- and interchain interactions of PEDOT chains and thus increases the π-electron accumulation on Ga-PP chains, which facilitates improvement of the electron storage of Ga-PP and its noncontact sensing ability. The water solubility of the obtained Ga-PP can reach approximately 15 mg/mL, comparable to that of commercial PEDOT:PSS, thus making Ga-PP suitable for various design strategies to prepare EF-NFE devices. We demonstrate that a conductive textile with a noncontact sensing ability can be achieved by immersing a commercial silk fabric into a Ga-PP solution for 5 min. With a detection distance exceeding 1 m, the prepared Ga-PP-based conductive textile (Ga-PP-CT) possesses outstanding noncontact sensing sensitivity, showing advantages in tracing the locations of signal sources and distinguishing motion states. Surprisingly, even when placed in water, Ga-PP-CT can be used to monitor the movement signals of athletes in different sporting events and output specific noncontact response signals for different sports. Intriguingly, the Ga-PP solution itself can be used to construct noncontact sensing conductive circuits, displaying the potential to be incorporated into smart electronics.
更多
查看译文
关键词
EGaIn,PEDOT:PSS,electric field,liquid metal,noncontact sensing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要