Reprocessing cassiterite tailings using gravity preconcentration, comminution with efficient classification, and single stage gravity separation of the liberated minerals
This paper addresses a longstanding, four-decade, problem in recovering cassiterite from tailings. The tailings feed had a grade of 0.3 wt.% tin, liberation size of 45 microns, with ~50% of the tin finer than 20 microns, and the rest distributed over a particle size range to ~300 microns. The feed was subjected to preconcentration using a 4th Generation REFLUX Classifier, achieving a mass rejection of 95 ±1%, grade of 2.8 ±0.1% tin, and overall tin recovery of 48 ±4% (tin recovery of 80% beyond 20 microns). With such a high mass rejection, there was insufficient material to feed the second stage. Hence, it was necessary to source alternative concentrate from the operation at the mine, at a reduced grade of 1.7% tin. This preconcentrated material was then subjected to efficient classification using a modified REFLUX Classifier, a GradePro, as part of a simulated milling circuit. The key feature of the classification was the elimination of by-pass, hence the avoidance of overgrinding. The milled concentrate then underwent gravity separation in a GradePro, achieving a further 94 ±0.5% mass rejection, further upgrade of 15, and recovery of 89 ±1%. The approach adopted in this study offers a powerful approach to achieving liberation, recovery, and very significant upgrade, offering a viable and efficient alternative to conventional multi-stage processing, particularly for low-grade ores or tailings.
Authors
- K.P. Galvin (ORCID: https://orcid.org/0000-0003-0450-9990)
- Margaret Amosah
Institutions
- ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals (AU)
- University of Newcastle Australia (AU)
Publication Details
- Journal
- Minerals Engineering
- Published
- 2026-11-02
- DOI
- https://doi.org/10.1016/j.mineng.2026.111028
- Primary Topic
- Mineral Processing and Grinding
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- FLSmidth
- Australian Research Council