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Mineralogical Characterization of Sieved and Un-Sieved Samples

In the field of extractive metallurgy, mineral processing, also known as mineral dressing or ore dressing, is the process of separating commercially valuable minerals from their ores and it consists of a number of interrelated procedures. In the past, mineral processing was done by hand, while in modern times it is typically achieved through the use of heavy machinery. And modern mineral processing techniques typically use mechanized unit processes to separate minerals from ore.

In order to determine the mineral quantities, liberation and association, mineralogical characterization is applied to mineral processing. And now automated mineralogical characterization by instruments such as the QEM * SCAN, the MLA and the TIMA is now quite widespread.

In this paper, the authors collected samples around the flotation rougher lead concentrator circuit, which were the feed, the concentrate and the tailings of this rougher circuit. Then one representative portion of the samples was left un-sieved. Another representative portion of the samples were sieved into six size fractions. Next polished sections were prepared for each of the un-sieved samples and also for their respective size fractions. Then image analyzer was used to measure the area of each particle and calculate the particle size as the square root of the particle area and some mineral quantities were presented. And liberation of galena in the feed, the concentrate and the tailings of the CuPb flotation circuit, differences between the liberation of galena from sized and from the un-sized samples and liberation of pyrite and the liberation of sphalerite in the CuPb concentrate were showed in figures.

In conclusion, detailed observation of the quantitative mineralogical data obtained using polished sections prepared with sieved and un-sieved samples indicated that there were differences in the mineral quantities and the mineral liberation. Nevertheless, it was noteworthy that it was possible to reach the same diagnostic conclusions with either set of data.

Article by Alfred Chioza and Shoji Ohga, from Kyushu University, Fukuoka, Japan.

Full access: http://mrw.so/RrSWX     
Image by Hannah Sue Gray, from Flickr-cc.

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