Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide

Hong, Xiaojiang and Lee, Jin Chai and Ng, Jing Lin and Abdulkareem, Muyideen and Md Yusof, Zeety and Li, Qiansha and He, Qian (2023) Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide. Nanomaterials, 13 (1405). pp. 1-19.

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Abstract

The excellent performance of graphene oxide (GO) in terms of mechanical properties and durability has stimulated its application potential in high-strength lightweight concrete (HSLWC). However, more attention needs to be paid to the long-term drying shrinkage of HSLWC. This work aims to investigate the compressive strength and drying shrinkage behavior of HSLWC incorporating low GO content (0.00–0.05%), focusing on the prediction and mechanism of drying shrinkage. Results indicate the following: (1) GO can acceptably reduce slump and significantly increase specific strength by 18.6%. (2) Drying shrinkage increased by 8.6% with the addition of GO. A modified ACI209 model with a GO content factor was demonstrated to have high accuracy based on the comparison of typical prediction models. (3) GO not only refines the pores but also forms flower-like crystals, which results in the increased drying shrinkage of HSLWC. These findings provide support for the prevention of cracking in HSLWC.

Item Type: Article
Uncontrolled Keywords: : drying shrinkage; modified prediction model; pore structure; microstructure; high-strength lightweight concrete; shale ceramsite; graphene oxide
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Civil Engineering and Built Environment > FKAAB
Depositing User: Mr. Mohamad Zulkhibri Rahmad
Date Deposited: 03 Sep 2024 08:49
Last Modified: 03 Sep 2024 08:49
URI: http://eprints.uthm.edu.my/id/eprint/11560

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