材料科学
复合材料
纳米复合材料
压阻效应
石墨烯
聚氨酯
模数
纳米技术
作者
Mahdokht Kadkhodazadeh,Saeed Pourmahdian,Faramarz Afshar‐Taremi
摘要
Abstract Strain sensors with high elasticity and toughness have attracted significant interest for applications requiring materials integrated with artificial intelligence. Over the past decade, extensive research has been conducted into flexible wearable electronics that demonstrate a high sensitivity of electrical resistance to strain. In this study, we synthesized polyurethane (PU) with a high elastic modulus (), utilizing poly (tetramethylene ether) glycol (PTMEG, 2000 D) and polyethylene glycol (PEG, 400 D). Multiwalled carbon nanotubes (MWCNT or CNT) and graphene, incorporated at a concentration of 0.75 wt.%, served as conductive fillers close to the electrical percolation threshold. The nanocomposites composed of CNT and Graphene exhibited a relative resistance increase of approximately 500% as they neared the percolation threshold. In contrast, the hybrid nanocomposite demonstrated even greater sensitivity to strain, achieving a relative resistance of 1600% and showcasing a more extended linear region. Furthermore, the storage modulus () of the PU and its nanocomposites indicated high thermal stability, remaining above 10 MPa at 150°C, with an ultimate strength () exceeding 69 MPa at room temperature. The specimens' cyclic performance revealed that the piezoresistance hysteresis and stress–strain behavior stabilized after the second cycle. These results suggest that the hybrid nanocomposite is a promising candidate for use as a strain sensor, exhibiting a high linear response up to a strain of 12%. Highlights High‐modulus PU with high thermal stability was synthesized. Nanocomposites of graphene and MWCNT were prepared. The hybrid nanocomposite showed high strain sensitivity for piezo‐resistance. Cyclic relative resistance showed low hysteresis.
科研通智能强力驱动
Strongly Powered by AbleSci AI