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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Mdpi
2023
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| Online Access: | http://eprints.uthm.edu.my/9584/ http://eprints.uthm.edu.my/9584/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf |
| _version_ | 1848889717372747776 |
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| author | Xiaojiang Hong, Xiaojiang Hong Jin Chai Lee, Jin Chai Lee Jing Lin Ng, Jing Lin Ng Abdulkareem, Muyideen Md Yusof, Zeety Qiansha Li, Qiansha Li Qian He, Qian He |
| author_facet | Xiaojiang Hong, Xiaojiang Hong Jin Chai Lee, Jin Chai Lee Jing Lin Ng, Jing Lin Ng Abdulkareem, Muyideen Md Yusof, Zeety Qiansha Li, Qiansha Li Qian He, Qian He |
| author_sort | Xiaojiang Hong, Xiaojiang Hong |
| building | UTHM Institutional Repository |
| collection | Online Access |
| 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 |
| first_indexed | 2025-11-15T20:30:37Z |
| format | Article |
| id | uthm-9584 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:30:37Z |
| publishDate | 2023 |
| publisher | Mdpi |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-95842023-08-02T03:53:34Z http://eprints.uthm.edu.my/9584/ Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide Xiaojiang Hong, Xiaojiang Hong Jin Chai Lee, Jin Chai Lee Jing Lin Ng, Jing Lin Ng Abdulkareem, Muyideen Md Yusof, Zeety Qiansha Li, Qiansha Li Qian He, Qian He 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/9584/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf Xiaojiang Hong, Xiaojiang Hong and Jin Chai Lee, Jin Chai Lee and Jing Lin Ng, Jing Lin Ng and Abdulkareem, Muyideen and Md Yusof, Zeety and Qiansha Li, Qiansha Li and Qian He, Qian He (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 |
| spellingShingle | T Technology (General) Xiaojiang Hong, Xiaojiang Hong Jin Chai Lee, Jin Chai Lee Jing Lin Ng, Jing Lin Ng Abdulkareem, Muyideen Md Yusof, Zeety Qiansha Li, Qiansha Li Qian He, Qian He Prediction Model and Mechanism for Drying Shrinkage of High-Strength Lightweight Concrete with Graphene Oxide |
| title | 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_short | 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 |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/9584/ http://eprints.uthm.edu.my/9584/ http://eprints.uthm.edu.my/9584/1/J16091_1a5b1a8b7dd277dfdc559f41d422a754.pdf |