Influence of polyurethane coating thickness on sulfate attack resistance of cement mortars and corrosion resistance prediction modeling

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Authors: Chao Xie, Yufeng Shi, Ping Wu, Binqiang Sun
Cited by: 0

Abstract

To investigate the effect of polyurethane (PU) coating thickness on the corrosion protection performance of cement-based materials under sulfate attack and establish a predictive model for the corrosion resistance of coated cement-based composites, specimens of cement mortar coated with PU layers of varying thicknesses (30–120 μm) were prepared in this study. The development of flexural strength in these coated cement mortar composites under sulfate attack was systematically studied. Concurrently, the corrosion resistance of each group of specimens under sulfate attack was analyzed using techniques such as nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The results indicated that the sulfate attack resistance of PU-coated cement mortar specimens exhibited a trend of initial improvement followed by a decline with increasing coating thickness. The optimal protective effect was achieved at a coating thickness of 90 μm. This group of specimens demonstrated the least deterioration in surface morphology and pore structure, with a flexural strength loss rate of only 9.69% after 180 days of sulfate attack. Based on the experimental results and existing research, this study elucidated the mechanism underlying the influence of coating thickness on the corrosion resistance of coated cement mortar. Furthermore, a predictive model for the corrosion resistance of coated cement mortar was established. The model showed high agreement between calculated and measured values, with an average error of 3.51%, allowing accurate predictions of the changes in flexural strength of specimens at various corrosion ages.

Fields of Study & Subjects

Concrete Corrosion and Durability Concrete and Cement Materials Research Corrosion Behavior and Inhibition

Publication details

Journal / source
Figshare
Publication date
11 March 2026
Language
EN