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Crystalline Admixtures for Self-Healing Cementitious Composites: A Comparative Review of Experimental Studies

Oct 2026 · The Open Construction & Building Technology Journal · Vol 20 · 0 citations · 97 references

Abstract

Cracking remains a major durability problem in cement-based materials because it facilitates the ingress of water and aggressive agents, accelerating deterioration. Crystalline Admixtures (CAs) have gained attention as a moisture-activated self-healing approach because they promote the formation of insoluble products within pores and cracks, thereby reducing crack connectivity and improving water tightness. This review compares the experimental evidence on CA-containing cementitious materials identified through manual searches of Scopus, Web of Science, and Google Scholar. Studies relevant to CA-assisted crack sealing, permeability or water-tightness recovery, mechanical recovery, durability performance, and microstructural changes were screened and comparatively evaluated. Evidence strength was assessed qualitatively according to the reporting of CA dosage, crack characteristics, healing conditions, test procedures, and quantitative outcomes, with greater confidence given when visual crack closure was supported by functional measurements. A central contribution of the review is the explicit distinction between direct crack-healing studies, durability-recovery studies, and durability-only investigations on uncracked specimens, thereby avoiding interpretation of different forms of evidence as equivalent. Across the reviewed literature, the most consistent benefit of CAs was improvement in water tightness and reduced permeability, while mechanical recovery was less consistently demonstrated. Healing was more consistently reported for relatively small cracks, particularly below approximately 0.3-0.4 mm, under water-rich or wet-dry conditions, whereas wider cracks showed greater dependence on moisture availability, healing duration, and hybrid approaches. The review identifies standardized testing, improved assessment of internal healing, CA-specific predictive modeling, optimized hybrid systems, and long-term field validation as major priorities for future research.

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