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

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...

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Main Authors: Hong, Xiaojiang, Lee, Jin Chai, Ng, Jing Lin, Abdulkareem, Muyideen, Md Yusof, Zeety, Li, Qiansha, He, Qian
Format: Article
Language:English
Published: Mdpi 2023
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/11560/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf
http://eprints.uthm.edu.my/11560/
https://doi.org/10.3390/nano13081405
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spelling my.uthm.eprints.115602024-09-03T08:49:08Z http://eprints.uthm.edu.my/11560/ Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide Hong, Xiaojiang Lee, Jin Chai Ng, Jing Lin Abdulkareem, Muyideen Md Yusof, Zeety Li, Qiansha He, Qian T Technology (General) 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. Mdpi 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/11560/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf 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. https://doi.org/10.3390/nano13081405
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Hong, Xiaojiang
Lee, Jin Chai
Ng, Jing Lin
Abdulkareem, Muyideen
Md Yusof, Zeety
Li, Qiansha
He, Qian
Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
description 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.
format Article
author Hong, Xiaojiang
Lee, Jin Chai
Ng, Jing Lin
Abdulkareem, Muyideen
Md Yusof, Zeety
Li, Qiansha
He, Qian
author_facet Hong, Xiaojiang
Lee, Jin Chai
Ng, Jing Lin
Abdulkareem, Muyideen
Md Yusof, Zeety
Li, Qiansha
He, Qian
author_sort Hong, Xiaojiang
title Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
title_short Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
title_full Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
title_fullStr Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
title_full_unstemmed Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide
title_sort prediction model and mechanism for drying shrinkage of high-strength lightweight concrete with graphene oxide
publisher Mdpi
publishDate 2023
url http://eprints.uthm.edu.my/11560/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf
http://eprints.uthm.edu.my/11560/
https://doi.org/10.3390/nano13081405
_version_ 1811687199793479680
score 13.223943

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