Slurry rheology prediction based on hyperspectral characterization models for minerals quantification

- Rheology is a key input variable for processes were fluids are involved.
- Mineralogical variations affect the rheology of slurries.
- Rheology measurements were conducted for slurries with controlled composition.
- XRD and hyperspectral characterization was made for dried slurries.
- Prediction of rheological properties from hyperspectral data performed well.

The presence of clays in mineral processing offers a number of challenges that range from valuable species recovery to the transport of tailings. In particular, when the abundance of one or more clay types increases, the rheology may be significantly affected. In this paper, the feasibility of using hyperspectral characterization to estimate rheological properties of mineral suspensions was studied. Towards this purpose, a set of rheology measurements was made for slurries of different composition, combining up to three out of five minerals: three clay minerals (two bentonites from different sources and kaolin), quartz and white mica, which are the main gangue minerals present in the Chilean copper mining industry. Using a Bingham Plastic flow model, a set of ternary plots for Bingham viscosity and yield stress was obtained. Results show counter-intuitive behavior for kaolin-white mica mixtures, showing a minimum for viscosity at a 2:3 ratio respectively. In addition, mechanisms for lowering the high viscosity reached by bentonite slurries were assessed. Modelling of the hyperspectral data produced high accuracy estimates of the mineral abundances, enabling an accurate determination of the respective samples position in the ternary mineralogy-rheology diagrams.

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