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Electron Microscopy Solutions

Ore Characterization

An elemental and mineral deportment analysis solution

Modern mining production faces a wide variety of operational challenges. While ore bodies are becoming increasingly complex,  both from a mineralogical and textural perspective, as grades continue to decline, the sustainability of mining requires that more care is to be taken with penalty elements. As a result, elemental and mineral deportment is becoming a critical requirement for ore characterization projects. Automated mineralogy is the turnkey solution for elemental and mineral deportment analysis.

Challenges in Ore Characterization

The overall grade of many common ore types is gradually declining. For example, copper ore bodies at Cu-grades >5% with bornite as the primary copper mineral species are no longer the rule but the exception. Much more common are copper ores of 1% copper grade, with a multitude of copper sulphides contributing to copper grade, such as chalcocite, chalcopyrite and covalite. As a result, plant operators are increasingly challenged to understand which minerals actually contribute to grade, as each mineral is likely to behave differently to comminution, flotation or leaching.

Elemental deportment also entails the comprehensive understanding of minerals that do not contribute to grade, as well as penalty elements that can cause environmental concerns with tailings storage (e.g. Arsenicum), affect the efficiency of processing (e.g. hydrophobic gangue minerals such as talc), or affect the value of the final concentrate (e.g. bismuth in a copper sulphide concentrate, or chrome in a PGM concentrate). 

Traditional bulk geochemical analysis techniques such as AA, ICP or XRF do not offer a capability to measure elemental deportment -- XRD and automated mineralogy do. In addition, automated mineralogy also provides the textural context of elemental and mineral deportment.

A Portfolio of Automated Mineralogy Solutions

Leading mining companies such as Anglo Platinum, Freeport McMoran and Rio Tinto were among the early adaptors of automated mineralogy, collecting years of monthly or weekly composites of feed, concentrate and tailings samples. These vast databases of ore properties have been correlated to plant performance, which in each case has led to a revised insight of ore classification. This was historically done on the basis of input from geologists and mineralogists, yet some of the geological ore differences did not translate into different processing behaviors. Instead, automated mineralogy data coupled to plant data has led to revised insight of classifying ore types on the basis of metallurgical properties, i.e. processing domains that are metallurgically meaningful. In many documented instances, the enhanced understanding of ore properties has led to major investments with enormous returns in e.g. new grinding technologies or plant upgrades. In addition, the knowledge is stored in a database for future reference and to be used for comparative studies when plants experience high losses to tailings, which drives a key requirement for Automated Mineralogy, namely compatibility with historical data.

Thermo Fisher Scientific serves ore characterization requirements of the mining companies with a portfolio of automated mineralogy laboratory and field systems, both QEMSCAN and MLA, on four different SEM platforms, to provide tailored solutions to throughput requirements, turnkey solutions for certain ore types (e.g. low grade), basic analysis resolution, and ruggedness for fast turn-around on-site geometallurgical programs.

Products for Ore Characterization

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