Recycling and Value-Added Utilization of Bayan Obo Tailings: Mechanisms, Technologies, and Prospects

As the largest processing residue from a polymetallic paragenetic ore deposit in China, Bayan Obo tailings are rich in valuable resources such as rare earths, niobium, iron, and fluorite. Their efficient recovery and value-added utilization are of great significance for resource security and environmental protection. This paper systematically reviews the resource characteristics, recovery technologies, value- added utilization pathways, and underlying mechanisms related to Bayan Obo tailings, and provides an outlook on future development directions. Research shows that the tailings contain an average rare earth oxide (REO) grade of 7%, niobium pentoxide (Nb2O5) grade of 0.138%, and fluorite (CaF2) grade of 22.28%, indicating substantial resource potential. Physical separation, chemical extraction, and combined processes can be applied to recover valuable components, though recovery efficiency remains constrained by factors such as fine mineral particle size and complex mineral intergrowth. Utilizing tailings as a primary raw material for producing high-value-added products like glass ceramics, catalytic materials, and adsorbents represents an effective pathway for value-added utilization. The paper focuses on mechanisms involving Fe, rare earth elements (La, Ce), and Nb during material synthesis, such as Fe3+/Fe2+ transformation promoting crystallization of magnetite, La/Ce composite oxides inducing the formation of nano-clusters, and Nb2O5 acting as a nucleating agent to refine grain size. Finally, in response to current technical challenges in tailings utilization, future research directions are proposed, including the development of efficient and green extraction technologies, in-depth study of multi-component synergistic utilization mechanisms, and the production of high-end material products. At the same time, the potential applications of artificial intelligence (AI) technology in intelligent tailings sorting, process optimization, material design, and other related fields will be further explored, while new directions for intelligent and high-value utilization of tailings resources empowered by AI will be envisioned.