higher residual moisture. In contrast, coarser or better‑graded materials often respond more favorably to filtration systems. The dataset compiled in Figure 2 encompasses PSD curves from a broad set of tailings types reported in the literature, including successful filtered tailings case histories (AMEC, 2010), iron and lithium tailings (Grosso et al., 2021), gradation envelopes for dry‑stack operations (Crystal & Hore, 2018), gold tailings (Burden, 2021), graphite tailings (Moshi et al., 2019), polymetallic tailings from the Hecla Creek TDF (Erickson et al., 2021), and iron ore tailings from multiple sites (Costa et al., 2021; Amoah et al., 2018). By consolidating these sources, Meneses et al. (2024) establish a comparative PSD baseline that illustrates how different tailings materials align with or deviate from filtration performance thresholds. This benchmarking step forms a key component of their first‑pass filterability screening approach. Figure 2: Geotechnical Screening Method to Assess Filtration of Tailings (after Meness et al., 2024) 1.2. Clay Mineralogy and Atterberg Limits Clay content and mineralogy—particularly the presence of smectite or bentonitic clays—play a dominant role in tailings plasticity, suction behavior, and filter performance. Key insights: • Clay mineral type affects swelling potential, water adsorption, and shrink–swell behaviour under cyclic wetting/drying. • Atterberg limits provide indicators of plasticity; high plasticity index (PI) tailings exhibit lower permeability and may form weaker cake structures with higher residual moisture. • Suction sensitivity: Clay-rich tailings may undergo significant strength loss with small increases in degree of saturation—crucial for unsaturated stability assessments.
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