Issue |
MATEC Web Conf.
Volume 364, 2022
International Conference on Concrete Repair, Rehabilitation and Retrofitting (ICCRRR 2022)
|
|
---|---|---|
Article Number | 05012 | |
Number of page(s) | 7 | |
Section | Developments in Concrete Material Technology, Assessment and Processing | |
DOI | https://doi.org/10.1051/matecconf/202236405012 | |
Published online | 30 September 2022 |
Design of smart cementitious composites based on multi-walled carbon nanotubes (MWCNTs) using probe ultrasonicator for dispersion
LMDC, Université de Toulouse, INSA, UPS Génie Civil, 135 Avenue de Rangueil, 31077, Toulouse Cedex 04, France
* Corresponding author: shahzad@insa-toulouse.fr
The purpose of this study is to develop smart cementitious material by incorporating multi-walled carbon nanotubes (MWCNTs). Two different types of carbon nanotubes (CNT) were dispersed using probe ultrasonicator; (i) Pristine CNT (P-CNT), and (ii) Functionalized CNT through annealing (A-CNT). Percolation threshold and optimum content of CNTs were determined by measuring electrical resistivity, porosity, compressive and flexural strengths at various contents of CNTs (0, 0.5 %, 0.75 %, and 1 % with respect to mass of cement). Self-sensing study was also carried out on smart material by relating the electrical properties with cyclic compressive loading. For this purpose, the electrical response was recorded with Wheatstone Bridge (WSB) circuit. The effect of curing and saturation degree of specimens on the resistivity pattern was also discussed. The results of electrical resistivity and mechanical properties showed that the content of CNTs should be at least 0.75 % to develop smart cementitious materials with a significant sensitivity and without detrimental effect on the mechanical properties. Moreover, smart material incorporating pristine CNT provides better sensitivity of self-sensing response as compared to the annealed CNT. Self-sensing test results also showed that with the increase in the content of CNT, sensitivity and repeatability of the sensing response were improved.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.