Recovery of Rare Earth Elements from Acid Mine Drainage with Supported Liquid Membranes: Impacts of Feedstock Composition for Extraction Performance.

Acid mine drainage (AMD) from inactive coal mines can be enriched in rare earth elements (REEs) and has gained much attention as an alternative source for these technology-critical metals. However, AMD is a relatively low-grade REE resource in which the abundance of impurities and the composition variability of the feedstock create major uncertainties for the performance of REE extraction technologies. This study sought to identify AMD feedstock variables that influence the extraction efficiency of REEs by supported liquid membranes (SLMs). SLM separation is a process involving a hydrophobic membrane embedded with an extracting solvent that facilitates the selective extraction of REE ions. The major aims were to (1) assess the effectiveness of SLM-based REE separation from several AMD samples representing a spectrum of aqueous composition, (2) determine the effects of AMD storage and holding time on extraction performance, and (3) assess the impact of AMD pretreatment (e.g., filtration and pH adjustment) on REE recovery. The results showed that relative extraction fluxes of REE correlated with AMD characteristics such as pH and major ions such as Fe, Ca, and Mn. The purity of the acid strippant product, expressed as the REE dry weight content, depended on the initial REE concentrations in the AMD source rather than the flux of individual REEs across the membrane. For AMD samples stored for 3 months prior to extraction, REE recovery by SLM separations was substantially decreased if oxidation of Fe(II) to Fe(III) was observed during sample storage. Pretreatment of AMD feedstocks by pH adjustment did not substantially improve the separation performance. Overall, this study establishes primary water quality parameters of AMD that influence the SLM separation flux and product purity. Such insights contribute to a mechanistic understanding of critical metals extractions by SLM for complex and nontraditional feedstocks such as AMD wastes.

Duke Scholars

Author Heileen Hsu-Kim Civil and Environmental Engineering