Abstract

Slurries are widely used in mineral processing and their rheological properties such as viscosity and yield stress strongly determine the energy consumption for pumping, the water requirements for transport, the throughput rate of thickeners and the capacity constraints of tailings impoundments. To investigate the impact of the mineralogy on their rheological behavior, synthetic slurries were prepared by varying the content of bentonites and white mica in order to represent critical gangue minerals that affect the slurry rheology and which are associated with copper sulphides in Chilean ore deposits. Laboratory scale rheometries were performed using those slurries, and viscosity and yield stress were determined by applying a Bingham-plastic flow model, the most suitable according to the observed behavior. The rheological properties for slurries were plotted on ternary diagrams where gangue component amounts represent the axes. Both viscosity and yield stress showed synergistic behavior as a result of blending. After this, HyLogger3 hyperspectral characterization of dry slurry samples was conducted to study the feasibility of using this novel technology as a tool to quickly identify the above gangue minerals, which can cause deleterious effect during their transport as mixed slurry. Hyperspectral data was related to the information from rheometries such that predictive geometallurgical models are formulated by different modelling techniques. The modelling results confirmed a good accuracy in the quantification of minerals and prediction of rheological properties by using hyperspectral technology, thus leading the development of a reliable prediction tool for the viscosity and yield stress of mineral slurries.