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Get Free AccessSelf-powering and self-sensing concrete materials are critical for advancing intelligent civil infrastructure, particularly in powering various sensors used in structural health monitoring (SHM). This study developed an integrated cement-based triboelectric nanogenerator (TENG) and piezoresistive self-sensing sensors using fully cured nano carbon black (NCB)-reinforced cement mortar. In the cement-based TENG (CBTENG), a thin cement plate served as the positive triboelectric layers, while a polytetrafluoroethylene (PTFE) plate served as the negative triboelectric layers. The electrical output voltage increased with both the loading frequency and surface contact area. At a frequency of 4.0 Hz, the 40 mm × 40 mm × 5 mm CBTENG generated a short-circuit current of 8.2 μA and an open-circuit voltage of up to 113 V. This output was sufficient to recharge a 10 µF capacitor to 0.32 V within 25 seconds after rectification. A comparison of the triboelectric performance of CBTENGs with different surface areas revealed that larger specimens had a lower percentage of effective contact area. This was attributed to the uneven surfaces of both the cement-based and PTFE plates, as well as small protrusions and holes on the cement-based surface. The piezoresistive cement-based sensors demonstrated excellent self-sensing capabilities under various loading amplitudes, rates, and conditions, including both compression and bending. These sensors performed effectively whether used independently or embedded inside concrete beams. These findings pave the way for self-powering and self-sensing structure systems, leveraging triboelectric and piezoresistive effects to power sensors in smart civil infrastructure and SHM applications.
Wenkui Dong, Shuhua Peng, Kejin Wang, Yuhan Huang, Long Shi, Fan Wu, Wengui Li (2025). Integrated triboelectric self-powering and piezoresistive self-sensing cementitious composites for intelligent civil infrastructure. Nano Energy, 135, pp. 110656-110656, DOI: 10.1016/j.nanoen.2025.110656.
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Type
Article
Year
2025
Authors
7
Datasets
0
Total Files
0
Language
English
Journal
Nano Energy
DOI
10.1016/j.nanoen.2025.110656
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