Comparative Study of Iron Ore Characterisation by Optical Image Analysis and QEMSCANTM

In order to develop downstream processing routines for iron ore and to understand the behaviour of the ore during such processing, extensive mineralogical characterisation is required. To determine mineral associations, mineral liberation and grain size distribution, imaging techniques have to be used. There are two main imaging techniques used for the characterisation of iron ore, ie, Optical Image Analysis (OIA) and Scanning Electron Microscopy (SEM). In this article a QEMSCANTM system is used as an example of SEM methodology and results obtained from it are compared against results obtained by the CSIRO ‘Recognition3/Mineral3’ OIA system.Both OIA and QEMSCANTM systems have advantages and drawbacks. Even though the latest QEMSCANTM systems can distinguish between major iron oxides and oxyhydroxides, it is still problematic for QEMSCANTM to distinguish between iron ore minerals very close in oxygen content, eg haematite and hydroheamatite, or between different types of vitreous goethite.QEMSCANTM also can misidentify minerals with close chemical composition, ie haematite as magnetite and vitreous goethite as haematite. In OIA, iron minerals with slight differences in their oxidation or hydration state are more easily and directly recognisable by correlation with their reflectivity. In both methods, the presence of microporosity can result in some misidentification, but in SEM methods misidentifi cations due to microporosity can be critical. Low resolution during QEMSCANTM analysis can significantly affect the textural classifi cation of particle sections.The main conclusion of this study is that, for low iron content ores or tailings, QEMSCANTM can provide much more detailed information on the gangue minerals than OIA. However, for routine characterisation of iron ores with high iron content and containing a variety of iron oxides and oxyhydroxides, OIA is a faster, more cost-effective and more reliable method of iron ore characterisation. A combined approach using both techniques will provide the most detailed understanding of iron ore samples being characterised.