Optimization of the Proportioning and Microscopic Mechanism Study of Cement Mortar Prepared with Copper Tailings as Fine Aggregate
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| Publicado en: | Materials vol. 18, no. 11 (2025), p. 2569 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| Resumen: | To address the low resource utilization of copper tailings and high environmental impact of conventional river sand, this study innovatively integrates Box–Behnken design (BBD) with fractal theory to systematically investigate the performance optimization mechanisms of cement mortar incorporating copper tailings sand. A three-factor interaction model was developed through BBD experimental design, considering water–cement ratio (0.38–0.48), replacement ratio (10–30%), and binder–sand ratio (0.3–0.4), to elucidate the macroscopic performance evolution under multiparameter coupling effects. Fractal dimension analysis was employed to quantitatively characterize microstructural evolution. Experimental results demonstrate that the optimal parameters (water–cement ratio: 0.43, replacement ratio: 20%, binder–sand ratio: 0.35) yield superior performance, with 28-day compressive/flexural strengths reaching 61.88/7.14 MPa (12.3%/9.8% enhancement over the control group), and sulfate attack resistance showing 0.74% mass loss after 30 cycles. Microstructural analysis reveals reduced fractal dimension (D = 2.31) in copper tailings-modified specimens, indicating improved pore structure homogeneity. The enhanced performance is attributed to synergistic effects of micro-aggregate filling and pozzolanic reaction-driven C-S-H gel densification. This research establishes a novel multiscale methodology overcoming the limitations of conventional single-factor analysis, providing theoretical and technical support for high-value utilization of industrial solid wastes in construction materials. |
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| ISSN: | 1996-1944 |
| DOI: | 10.3390/ma18112569 |
| Fuente: | Materials Science Database |