Estimation of the liberation size of graphite in a schistose rock and its response to beneficiation

Patil, M. R.; Shivakumar, Kaushik; Prakash, S.; Rao, R. Bhima

doi:10.1007/bf03402777

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“…As mineral beneficiation is both energy and cost intensive, graphite raw materials and beneficiation products need to be characterised very carefully to optimise the beneficiation process chain. Currently, graphite raw materials are characterised using optical microscopy, X-ray powder diffraction (XRD), differential thermal analysis/thermogravimetry (DTA/TG), Raman spectroscopy, secondary ion mass spectrometry (SIMS) as well as chemical analysis (see, for example, Kwiecinska et al, 2010;Patnaik et al, 1999;Volkova et al, 2011;Patil et al, 1997).While these analytical methods provide a host of relevant information, only optical microscopy will provide at least some information about mineral association, liberation or locking, and all attributes relevant parameters to understand the success of beneficiation. However, optical microscopy is very time-consuming and thus expensive, with results often biased by the human factor.…”

Section: Introductionmentioning

confidence: 99%

Characterisation of graphite by automated mineral liberation analysis

Sandmann

Haser

Gutzmer

2014

Mineral Processing and Extractive Metallurgy

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The beneficiation of graphite is very costly and energy intensive and can necessitate multiple processing steps, often including flotation. Products have to satisfy very stringent quality criteria. To decrease beneficiation costs, a careful characterisation of feed and concentrate materials is needed. This study elucidates the additional benefit of methods of automated SEM-based image analysis, such as mineral liberation analysis (MLA), in addition to 'traditional' methods [optical microscopy and X-ray powder diffraction (XRD)] for the analyses of graphite raw materials and processing products. Owing to the physical and chemical properties of the mineral graphite, samples require delicate sample preparation as well as particular backscattered electron (BSE) imaging calibration for automated image analysis. These are illustrated in this study. The results illustrate that SEM-based image analysis of graphite feeds and concentrates can provide accurate and reliable information for the graphite beneficiation process. This applies to both mineralogical characteristics and process relevant parameters.

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Section: Introductionmentioning

confidence: 99%