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Experimental Study of the Electrical Resistance of Graphene OxideReinforced Cement-Based Composites with Notch or Rebar

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1 School of Civil Engineering, Chongqing University, Chongqing, 400045, China

* Corresponding Author: Yangao Hu. Email: email

The International Conference on Computational & Experimental Engineering and Sciences 2023, 27(3), 1-1. https://doi.org/10.32604/icces.2023.09773

Abstract

This paper investigates the effects of graphene oxide (GO), notch depth, rebar, and load on the resistivity of cement paste and mortar. The electrical conductivity of GO/cement composite reaches its maximum value when the GO content is 0.03%, which is approximately 50% higher compared to the composite without GO. The resistivity of GO/cement composite shows significant changes with increasing load from 0 to 40 kN. The gauge factor for compressive loading varies from about 26 to 73 for different GO contents. Moreover, the resistivity variation with the notch depth in GO/cement is found to be much greater than that in GO/mortar reinforced by rebars. The findings of this study have implications for the design of self-sensing concrete in structural health monitoring. Further research in this area could benefit from the insights provided by this work.

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APA Style
Hu, Y. (2023). Experimental study of the electrical resistance of graphene oxidereinforced cement-based composites with notch or rebar. The International Conference on Computational & Experimental Engineering and Sciences, 27(3), 1-1. https://doi.org/10.32604/icces.2023.09773
Vancouver Style
Hu Y. Experimental study of the electrical resistance of graphene oxidereinforced cement-based composites with notch or rebar. Int Conf Comput Exp Eng Sciences . 2023;27(3):1-1 https://doi.org/10.32604/icces.2023.09773
IEEE Style
Y. Hu, “Experimental Study of the Electrical Resistance of Graphene OxideReinforced Cement-Based Composites with Notch or Rebar,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 27, no. 3, pp. 1-1, 2023. https://doi.org/10.32604/icces.2023.09773



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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