Spelling suggestions: "subject:"selfsensing cementitious composites"" "subject:"genosensing cementitious composites""
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Self-sensing cementitious composites with hierarchical carbon fiber-carbon nanotube composite fillers for crack development monitoring of a maglev girderDing, S., Wang, X., Qui, L., Ni, Y-Q., Dong, X., Cui, Y., Ashour, Ashraf, Han, B., Ou, J. 06 December 2022 (has links)
Yes / In view of high-performance, multifunctional and low-carbon development of infrastructures, there is a growing demand for smart engineering materials, making infrastructures intelligent. This paper reports a new-generation self-sensing cementitious composite (SSCC) incorporated with a hierarchically structured carbon fiber-carbon nanotube composite filler (CF-CNT), which is in-situ synthesized by directly growing CNT on CF. Various important factors including catalyst, temperature, and gas composition are considered to investigate their kinetic and thermodynamic influence on CF-CNT synthesis. The reciprocal architecture of CF-CNT not only alleviates the CNT aggregation, but also significantly improves the interfacial bonding between CF-CNTs and matrix. Due to the synergic and spatially morphological effects of CF-CNT, i.e., the formation of widely distributed multiscale reinforcement networks, SSCCs with CF-CNTs exhibit high mechanical properties and electrical conductivity as well as excellent self-sensing performances, particularly enhanced sensing repeatability. Moreover, the SSCCs with CF-CNTs are integrated into a full-scale maglev girder to devise a smart system for crack development monitoring. The system demonstrates high sensitivity and fidelity to capture the initiation of cracks/damage, as well as progressive and sudden damage events until complete failure of the maglev girder, indicating its considerable potential for structural health monitoring of infrastructures. / The work described in this paper is supported by grants from the National Science Foundation of China (51978127 and 51578110) and grants from the China Postdoctoral Science Foundation (2022M710973 and 2022M720648).
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