At the Sustainable Energy and Minerals Research Group, our research spans the entire value chain of mineral processing, with a focus on comminution and classification, mechanical activation of minerals, filtration and separation, and bulk solids flow modeling. We combine rheological and electrochemical characterization of particulate systems with high-resolution experimental techniques such as Positron Emission Particle Tracking (PEPT) for granular flow visualization and model validation. We employ advanced computational tools, including the Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), Finite Element Method (FEM), and Smoothed Particle Hydrodynamics (SPH), to simulate and optimize complex multiphase systems. Our work integrates physical modeling with data science, particularly in creating machine learning-enabled digital twins for milling and classification units. These digital twins enhance real-time process monitoring and refinement of mineral liberation circuit performance, facilitating more efficient, predictive, and adaptive plant operation.

In the energy sector, we explore sustainable applications of industrial waste. This involves repurposing metallurgical slags as cost-effective thermal energy storage (TES) materials in Concentrated Solar Power (CSP) systems and valorizing coal refuse for use in pozzolanic cement production, thereby contributing to reduced emissions and innovation in the circular economy. We are affiliated with the Energy Institute (EI) and the Alliance for Education, Science, Engineering and Design with Africa (AESEDA), supporting global knowledge exchange and capacity building in science and engineering.

We collaborate with a global network of institutions, including MINTEK South Africa, Fraunhofer ITWM Germany, University of South Australia, the Julius Kruttschnitt Mineral Research Centre (JKMRC) at the University of Queensland, Australia, African University of Science and Technology (AUST) Nigeria, Moi University, Kenya, and Cape Peninsula University of Technology (CPUT), South Africa. Through the integration of computational modeling, nuclear imaging, machine learning, and sustainable minerals engineering, our research advances innovation at the intersection of mineral processing, energy systems, and data-driven industrial technologies.