Use of Scanning Electron Microscopy-Based Automated Quantitative Mineralogy for the Characterisation of Ni-Rich and Ni-Poor Goethite in Laterites

Nickel laterites constitute a significant proportion of the worldÆs Ni reserves and are considered environmentally friendly alternatives to traditional sulfide resources. Subsequently they are of increasing significance for exploration and production. To be successfully exploited, however, they require an understanding of the relations between mineralogy, texture, grade and recovery. The development of automated quantitative mineralogy can aid in the characterisation of the ores to help improve extraction and processing methods. Recent developments in hydrometallurgy have resulted in relatively straightforward recovery of Ni in silicate (saprolite and smectite) ores. However, the extraction of Ni from limonitic ores is more complex. It requires a detailed understanding of the iron-hydroxide species and other, potentially interfering, oxide and hydroxide compounds. Particularly the relations between the Ni-bearing goethite and Mn, Al and Cr may adversely affect the economic prospects of an ore. Manganese can adversely affect the selective recovery of Ni and Co from solutions but has also been highlighted as a significant potential by-product (cf, Zhang and Cheng, 2007). Aluminium hydroxides can be significant acid consumers leading to an increased expense of extraction (Johnson, Cashmore and Hockridge, 2005). Chromite is resistant to acid attack, but chromium in goethite may adversely affect the dissolution leading to a retention of Ni (McDonald and Whittington, 2008). This study presents an investigation of oxide and hydroxide species in laterites using QEMSCAN« EDS/SEM-based automated quantitative mineralogy. Samples were collected from Turkey (¦aldag), Albania and the Philippines. Particular emphasis has been placed on the development of a quantification for Ni-poor and Ni-rich goethite.