Controlling magnetic agglomeration in superconducting high gradient magnetic separation processing of iron ore tailings for high-grade silica recovery

Abstract

The superconducting high gradient magnetic separation (S-HGMS) technology can be used to effectively extract silica from iron ore tailings (IOTs). However, particle agglomeration in strong magnetic fields poses a challenge in achieving optimal performance. In this study, we investigated the agglomeration of IOT particles and the mechanisms for its inhibition through surface analysis, density functional theory (DFT), and extended Derjaguin-Landau-Verwey-Overbeek (EDLVO) theory. Hematite was found to exhibit the highest magnetic moment among the minerals present in IOTs, making it particularly prone to magnetic agglomeration. The addition of the dispersant SDSH into the slurry was essential in promoting the dispersion of IOT particles during the S-HGMS process. This dispersant hydrolyzed to form HPO₄^2- and RSO₃^- groups in the solution, which then chemically adsorbed onto the metal ions exposed on the surfaces of non-quartz particles, increasing interparticle electrostatic repulsion. Furthermore, the RSO₃^- groups physically adsorbed onto the surface of quartz particles, resulting in strong steric repulsion and enhancing the hydrophilicity of the particle surfaces, thereby inhibiting magnetic agglomeration between the particles. Under optimal conditions, the SiO₂ grade of the obtained high-grade silica powder increased from an initial value of 76.32% in IOTs to 97.42%, achieving a SiO₂ recovery rate of 54.81%, which meets the requirements for quartz sand used in glass preparation. This study provides valuable insights into the magnetic agglomeration of IOT particles and its inhibition while providing a foundation for regulating S-HGMS processes.

Keywords

Iron ore tailings / S-HGMS / High-grade silica powder / Magnetic agglomeration mechanism

Acknowledgments

This study was supported by USTB Institute for International People-to-People Exchange in Mining, Metallurgy and Metals Industries (No. FRF-IPPE-2404), and Scientific Research Platform Construction Fund for the Introduction of High-Level Talents at Kunming University of Science and Technology (No. CA25073M246A). We would also like to thank Qingya Li from Shiyanjia Lab for the XRD analysis.

Supplementary materials

Supplementary materials to this article can be found online at https://doi.org/10.1016/j.ijmst.2025.08.006.

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