Example of Ore Characterization by the use of Automated Mineralogical Analyses using Mineralogic Mining (ZEISS) technology: Results on the Hakkari samples (Turkey).

The Hakkari Zinc Project is a supergene nonsulfide Zn>>Pb deposit located in the Southeast of Turkey. Total resources estimated consist of 10 Mt @ 15% Zn. The ore concentrations mainly consist of oxidized Zn minerals (smithsonite and hemimorphite) derived from the weathering of sulphides, hosted in shallow water Jurassic limestone. This preliminary study is focused on the mineralogical and petrographic characterization of 4 Hakkari samples in term of quantitative modal mineralogy and average mineral association. The 4 samples were taken from different oxidation zones representative of the deposit, in order to characterize and quantify all the occurring mineral phases. The analyses were carried out by the use of a new generation of Automated Mineralogical Analyses system known as “Mineralogic Mining” (ZEISS), which utilizes modern quantitative EDS technology to allow minerals to be classified based on the % element abundance (stoichiometry). Previous QEMSCAN (FEI) analyses for the same 4 samples of the Hakkari mineralization (Santoro et al., 2014) provided a strong basis for the Mineralogic routine, and were used to assess the accuracy and the capabilities of Mineralogic system. Mineralogic Mining was able to build high-resolution maps and to clearly identify and quantify the major economic phases such as smithsonite and hemimorphite (up to ~58 wt.% and ~67 wt.% respectively in the analysed samples), and gangue phases as goethite (up to 38 wt.%). Minor phases such as barite (up to ~6 wt.%), dolomite (up to ~7 wt.%) calcite (up to ~8 wt.%), cerussite (up to ~8 wt.%), gypsum (up to ~1 wt.%), traces of pyrite, chalcophanite, hetaerolite, quartz, coronadite (<0.50 wt.%) were also detected in the analysed samples. It was also possible to identify the “impure” metal-bearing minerals: mainly Zn-enriched goethite (up to ~54 wt.%), but also traces of Zn-dolomite, Fe-dolomite, Mg-smithsonite, and Fe-smithsonite (<1 wt.%). The technique was clearly able to distinguish between two very similar mineral phases (i.e. ankerite and Fe-dolomite). The mineral association of the major mineral phases was also investigated. The results show that smithsonite and hemimorphite are generally associated together and with Zn-enriched goethite (in agreement with previous studies, Santoro et al., 2014). The software was also able to automatically calculate the distribution % of Zn in the different mineral phases, information which can be critical during geometallurgical modelling, feasibility studies and process planning, as it can help to predict metal losses during the treatment. The results on the analysed samples show that Zn occurs mostly in smithsonite, hemimorphite (as predictable) and in goethite (Zn-enriched goethite). This study revealed the effectiveness of the Mineralogic automated mineralogy system in ore characterisation, to be used during the feasibility studies in the exploration stage and processing modelling, as an early aid to the evaluation of possible recovery problems.