MoS2 nanoflowers and PEDOT:PSS nanocomposite enabling wearable dual-mode pressure sensors

• Published in: Science China. Technological sciences Vol. 67; no. 6; pp. 1737 - 1747
• Main Authors: Wang, FengMing, Yang, WeiJia, Ma, Ke, Shen, GengZhe, Su, DaoJian, Li, BaiJun, Wang, ShuangPeng, Qin, BoLong, Zhang, Chi, Xin, Yue, Cao, XiaoBing, He, Xin
• Format: Journal Article
• Language: English
• Published: Beijing Science China Press 01.06.2024; Springer Nature B.V
• Subjects: Engineering; Molybdenum disulfide; Nanocomposites; Polydimethylsiloxane; Pressure sensors; Response time; Sensitivity; Sensors; Substrates; MoS; physiological signals monitoring; object grasping recognition; multi-scaled microstructure; PEDOT:PSS nanocomposite; force-sensitive sensor
• ISSN: 1674-7321; 1869-1900
• DOI: 10.1007/s11431-023-2550-4

A versatile sensing platform employing inorganic MoS 2 nanoflowers and organic poly(3,4-ethylene dioxythiophene): poly (styrene sulfonate) (PEDOT:PSS) has been investigated to develop the resistive and capacitive force-sensitive devices. The microstructure of the sensing layer heightens the sensitivity and response time of the dual-mode pressure sensors by augmenting electron pathways and inner stress in response to mechanical stimuli. Consequently, the capacitive and resistive sensors exhibit sensitivities of 0.37 and 0.12 kPa −1 , respectively, while demonstrating a remarkable response time of approximately 100 ms. Furthermore, it is noteworthy that the PEDOT:PSS layer exhibits excellent adhesion to polydimethylsiloxane (PDMS) substrates, which contributes to the development of highly robust force sensitive sensors capable of enduring more than 10000 loading/unloading cycles. The combination of MoS 2 /PEDOT:PSS layers in these dual-mode sensors has shown promising results in detecting human joint movements and subtle physiological signals. Notably, the sensors have achieved a remarkable precision rate of 98% in identifying target objects. These outcomes underscore the significant potential of these sensors for integration into applications such as electronic skin and human-machine interaction.