Sensor-based Multi-Level Analysis of Ferronickel Furnace Slag: Exploring Economic Opportunities

The ever-growing demand for mining products has led to the extraction and processing of large volumes of materials, resulting in the production of significant amounts of mine waste. While the composition of mine waste materials can vary and may cause environmental impacts, they can also be a valuable source of raw materials to meet the current and future mineral demand. The efficient re-mining of minerals of economic interest from mine waste materials (such as slag) requires accurate and reliable estimation. This can be achieved using state-of-the-art sensor technologies coupled with advanced data analytics. Such technologies include laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence (XRF), short-wave infrared (SWIR) and Fourier transform infrared spectroscopy (FTIR). This study evaluates the usability of LIBS, FTIR, SWIR, and XRF technologies for the characterization of Ferronickel slag materials at a multi-level. Methodological approaches were developed to assess the usability of each technique for the identification, classification, or semi-quantification of the target elements (such as Ni, Ti, Pb, and Cr) in the analyzed samples. The results demonstrate that the use of the techniques enabled a comprehensive compositional analysis of slag materials. Moreover, the findings suggest that such an approach could promote sustainable mining practices by providing valuable insights into the potential economic benefits of reusing slag materials for secondary recovery. Such an approach could contribute to reducing the possible environmental impact of waste and could enable achieving a circular economy.