Analysis reveals nonlinear regression can predict coating adhesion strength in concrete, indicating surface roughness impacts performance.
This study systematically investigates the influence of concrete substrate surface texture characteristics on the adhesion strength of waterborne epoxy coatings. By employing surface treatment techniques such as brush scouring and grinding, the surface roughness, pore structure, and three-dimensional morphology of concrete substrates were quantitatively analyzed using laser scanning and parameter modeling. The correlation between texture parameters (e.g., three-dimensional arithmetic mean roughness Sa and proportion of the hole area) and coating adhesion strength under varying curing temperatures (−18 °C, 20 °C, 40 °C, and 60 °C) was evaluated through pull-off tests and Pearson Correlation Analysis. Results indicate that the absolute proportion of hole area (Aa) (r ≈ −0.93) and Sa (r ≈ −0.81) are key factors affecting adhesion. Surface treatments, including 5 h scouring and 40 min grinding, enhanced pull-off strength by 40–60% by optimizing mechanical interlocking. A nonlinear regression model was established to predict adhesion strength, suggesting an operational Sa range of approximately 0.35–0.40 mm for the current coating system at 20 °C. Temperature significantly modulated the adhesion mechanism; low-temperature curing exacerbated pore defects, while high-temperature conditions intensified thermal stress. Practical guidelines to improve permeability include optimizing the surface roughness through grinding, strictly controlling the absolute proportion of holes, and using preheated or low-viscosity resin in a low-temperature environment.
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Fan et al. (2025) studied this question.
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