Advanced Discrimination of Hematite and Magnetite by Automated Mineralogy

Abstract

Better mineral characterisation is required for reliable and quantitative characterisation of iron ore sources. Studying mineral liberation of hematite and magnetite is important to predict iron extraction behaviour. Similar elemental composition makes their discrimination by automated scanning electron microscopy/energy-dispersive x-ray spectroscopy (SEM-EDS) a challenge. Similar backscattered electron (BSE) intensities further complicate prior image segmentation performed by the Mineral Liberation Analyser (MLA) to better define energy-dispersive x-ray (EDX) spectra acquisition. Here, a new automated characterisation for hematite and magnetite is demonstrated, it involves 1) measurement parameter optimisation; 2) flexible EDX spectra acquisition of single geometric centre points or mapping on saturated segmented regions with a regular grid; and, 3) a new classification algorithm combining EDX and BSE characteristics. This automated SEM-EDS based approach is shown to accurately discriminate hematite from magnetite, and quantify mineral associations and locking without increasing considerably measurement times.