Characterization of the sedimentation and drying processes of complex mining tailings materials using NMR

Sedimentation and drying are important physicochemical processes that play critical roles in the management of mining operations, directly impacting environmental safety and operational efficiency. This study develops a methodology of utilizing portable single-sided nuclear magnetic resonance (NMR) instruments to study free and induced sedimentation as well as drying processes of complex tailings materials from gold mine tailings storage facilities (TSFs) <i>via</i> the detection of ¹H NMR water signals of the tailings. The results obtained are discussed considering the influence of the physical and mineralogical properties of tailings, such as particle-size distribution, mineral composition, and solid-content percentage. We observed various phases of sedimentation, including short-term and long-term sedimentations, which are characterized by significantly different timescales required for reaching the complete settling of the sludge layers. Moreover, we show that NMR allows the detection of an interesting effect of mechanically induced sedimentation, which is reported only scarcely in the literature. These findings demonstrate the complexity of the sedimentation process and support a clear relationship among the settling rate, particle size, and density of the minerals. In addition, by using a controlled aeration method on top of a single-sided NMR device, we could evaluate the dynamics of the drying process. The utilized NMR methodology is sensitive to slight changes in the water content and mobility <i>via</i> the measurements of both the ¹H NMR signal amplitudes and the <i>T</i>₂ relaxation times. It allows one to quantify the water content during the transition from slurry-like to sludge-like forms of the studied tailings. The findings can provide valuable tools to characterize tailings sedimentation and dewatering, highlighting the potential of portable NMR as an analytical tool for real-time monitoring and optimization of TSF management strategies.