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The efficient reprocessing of low-grade copper tailings remains a significant challenge in mineral processing due to complex mineralogical constraints and limited flotation selectivity. This study presents a novel mineralogy-informed optimization framework combining automated mineralogical analysis (SEM–TIMA) with Response Surface Methodology (RSM–CCD) an integration not previously applied to copper tailings from the Anti-Atlas metallogenic district of Morocco. SEM–TIMA revealed that copper predominantly occurs as micrometric sulfide and oxide phases (<30 µm), extensively intergrown with silicate–carbonate gangue minerals, with 96.99 % of copper bearing phases occurring as locked or partially encapsulated particles. Grain size, near total encapsulation, and the inherent refractoriness of chrysocolla to conventional sulfidation–xanthate flotation was identified as the principal mineralogical constraints governing flotation performance. RSM–CCD optimization of four operating variables PAX dosage, NaSH dosage, pulp solid concentration, and pH produced second order polynomial models with high predictive accuracy (R² = 0.964 for recovery; R² = 0.980 for grade). Under optimal conditions, a copper recovery of 63.72 % with a concentrate grade of 1.46 % Cu was achieved. This ceiling is governed by the inherent mineralogical character of the tailings, not by the reagent conditions applied. The integrated framework developed here can serve as a diagnostic tool for flotation circuit design in other fine-grained, oxide sulfide copper tailings systems.
Koucham et al. (Mon,) studied this question.