A State-of-the-Art Review on the Freeze–Thaw Resistance of Sustainable Geopolymer Gel Composites: Mechanisms, Determinants, and Models
Geopolymer, as a sustainable, low-carbon gel binder, is regarded as a potential alternative to cement. Freeze–thaw (F-T) resistance, which has a profound influence on the service life of structures, is a crucial indicator for assessing the durability of geopolymer composites (GCs). Consequently, com...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Gels |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2310-2861/11/7/537 |
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| Summary: | Geopolymer, as a sustainable, low-carbon gel binder, is regarded as a potential alternative to cement. Freeze–thaw (F-T) resistance, which has a profound influence on the service life of structures, is a crucial indicator for assessing the durability of geopolymer composites (GCs). Consequently, comprehending the F-T resistance of GCs is of the utmost significance for their practical implementation. In this article, a comprehensive and in-depth review of the F-T resistance of GCs is conducted. This review systematically synthesizes several frequently employed theories regarding F-T damage, with the aim of elucidating the underlying mechanisms of F-T damage in geopolymers. The factors influencing the F-T resistance of GCs, including raw materials, curing conditions, and modified materials, are meticulously elaborated upon. The results indicate that the F-T resistance of GCs can be significantly enhanced through using high-calcium-content precursors, mixed alkali activators, and rubber aggregates. Moreover, appropriately increasing the curing temperature has been shown to improve the F-T resistance of GCs, especially for those fabricated with low-calcium-content precursors. Among modified materials, the addition of most fibers and nano-materials remarkably improves the F-T resistance of GCs. Conversely, the effect of air-entraining agents on the F-T resistance of GCs seems to be negligible. Furthermore, evaluation and prediction models for the F-T damage of GCs are summarized, including empirical models and machine learning models. In comparison with empirical models, the models established by machine learning algorithms exhibit higher predictive accuracy. This review promotes a more profound understanding of the factors affecting the F-T resistance of GCs and their mechanisms, providing a basis for engineering and academic research. |
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| ISSN: | 2310-2861 |