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  5. A review study on encapsulation‐based self‐healing for cementitious materials

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Article
en
2018

A review study on encapsulation‐based self‐healing for cementitious materials

0 Datasets

0 Files

en
2018
Vol 20 (1)
Vol. 20
DOI: 10.1002/suco.201800177

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Ye Guang
Ye Guang

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Caihong Xue
Wengui Li
Jianchun Li
+2 more

Abstract

Encapsulation‐based self‐healing technology is an effective method for healing the crack‐deteriorated cementitious material. Encapsulation‐based self‐healing initiates by crack occurrence and progresses by chemical reaction of released self‐healing agents in the cracks, which are contained in capsules. In this paper, a review has been conducted on various healing agents, encapsulation techniques, as well as experimental approaches, basing on existing substantial studies. Recently, there is no consistent agreement on the effective criteria for evaluating encapsulation‐based self‐healing and mature solution for increasing the survival ratio of capsules during mixing. However, the polyurethane‐based healing agents filled in glass or ceramic tubes are popularly applied for self‐healing cementitious materials. Besides, the polymer capsules present promising attractions for engineering application. Mechanical strength and durability are the most widely used self‐healing efficiency assessment indexes. On the other hand, nondestructive technique and numerical modeling have also extensively adopted to visualize and evaluate the self‐healing behavior of cementitious materials. However, there are still some challenges, which require further investigations, such as behavior of crack propagation, kinetics of healing agent in discrete crack surfaces, effect of inserted capsules on the mechanical properties of self‐healed cementitious materials.

How to cite this publication

Caihong Xue, Wengui Li, Jianchun Li, Vivian W.Y. Tam, Ye Guang (2018). A review study on encapsulation‐based self‐healing for cementitious materials. , 20(1), DOI: https://doi.org/10.1002/suco.201800177.

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Publication Details

Type

Article

Year

2018

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/suco.201800177

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