Bayer red mud is a highly alkaline, fine-grained solid waste generated at ~180 million tons per year, posing persistent environmental hazards while containing recoverable Fe, Al, Ti, and rare earth elements. This review critically evaluates selective metal recovery from an environmental chemical engineering perspective. We link metal/alkali occurrence to leachability and selectivity, and position dealkalization as an essential pretreatment to mitigate hazards and enable downstream recovery. Pyrometallurgical, hydrometallurgical, and bio-based routes are compared for recovery performance, energy/carbon footprint, and secondary pollution risks. We further discuss prediction-guided optimization using artificial neural networks and atomistic simulations (DFT) to reduce trial-and-error and improve process transferability. Finally, we propose a hazard-controlled, closed-loop valorization framework integrating staged recovery, reagent/water recycling, and harmonized sustainability metrics. This review provides green guidance for transforming red mud from an environmental liability into a safer secondary resource.
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Gong et al. (2026) studied this question.
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