2026-10-13T00:25:03Z https://www.scidb.cn/oai

10.57760/sciencedb.j00125.00221 2026-07-16T15:58:29Z

2026-07-16 Silanised Multi-Walled Carbon Nanotubes for Shoulder Peak Optimisation and Sensitivity Enhancement in Butyl Rubber-Based Conductive Elastomer Composites doi:10.57760/sciencedb.j00125.00221 en Abstract: Conductive elastomer composites (CECs) hold great promise in the field of structural health monitoring (SHM) for seismic isolation bearings due to their excellent flexibility and stretchability. However, these materials generally suffer from the sensor response shoulder peak effect and insufficient sensitivity in the low-strain range, which severely limits their application in high-precision engineering monitoring. To overcome these limitations, this study employed a silane coupling agent (KH570) to surface-modify hydroxylated carbon nanotubes (MWCNTs-OH) and, through a solution blending process, combined them with butyl rubber (IIR) to successfully prepare the modified conductive elastomeric composite MHKIIR. The results indicate that silane modification of MWCNTs-OH significantly improves their dispersion stability in IIR and effectively regulates interfacial interactions within the composite material. The MHKIIR achieved complete elimination of the response shoulder within a 20% strain range and substantially improved response sensitivity across the entire sensing range; its sensitivity within the 20% sensing range was 513.41% higher than that of the unmodified system, while maintaining good signal stability and repeatability during 15,000 cycles of tensile-unloading testing. These results indicate that MHKIIR holds great promise for application in the field of long-term, high-precision structural health monitoring of seismic isolation bearings. Hydroxylated multi-walled carbon nanotubes; Silane coupling agents; Butyl rubber; Resistance-strain response; Structural health monitoring Jinxiong Zhang Yang Yang Rongxin Guo Intan Zaurah Mat Darus Yong Yan Yanfang Zhao Bangwei Wan PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank