2007 GSA Denver Annual Meeting (28–31 October 2007)

Paper No. 15
Presentation Time: 11:45 AM

ADVANCED MINERALOGY RESEARCH: MINERAL CHARACTERIZATION USING QEMSCAN® TECHNIQUES


HOAL, Karin O.1, BOTHA, Pieter W.S.K.2, FORSYTH, Adam3 and BUTCHER, Alan R.3, (1)Advanced Mineralogy Research Center, Colorado School of Mines, 1310 Maple St, Golden, CO 80401, (2)FEI Australia, 2/27 Mayneview St, Milton, Queensland, 4064, Australia, (3)Intellection Pty Ltd, 2/27 Mayneview St, Milton, Queensland, 4064, Australia, khoal@mines.edu

There is currently significant demand in industry for trained mineralogists, particularly optical microscopists with a good knowledge of mineralogy and geology. This demand reflects the low numbers of students with a strong foundation in mineralogy now available for hire, ironically at a time when mineralogy and optical mineralogy courses are disappearing from geology department curricula. Nevertheless, mineral characterization is critical to commercial geologic activities in minerals, mining, environmental, and oil and gas, wherever the compositions and textures of materials must be quantified and assessed. Automated mineralogy techniques take over where traditional optical microscopy and point counting cannot statistically accommodate the thousands of grains analyzed daily in large projects.

The Colorado School of Mines is developing the first Advanced Mineralogy Research Center, dedicated to research in mineral characterization, and to education and training opportunities in new applications in automated mineralogy. The primary tool for the Center is the QEMSCAN®, an electron-beam analytical instrument initially developed by the CSIRO and now produced by Intellection Pty Ltd. QEMSCAN® uses four nitrogen-free EDS x-ray detectors, BSE and SE analysis, and a proprietary software platform to capture a wide spectrum of elemental abundance data on a pixel basis, and image the data so they can be assessed as required. Developed for the mining industry, the instrument achieves rapid image analysis and data acquisition for thousands of grains in a short time, enabling quick assessment of compositional variation, distribution, grain shape, and mineral assemblages. It is applied to the analysis of mineralogy, alteration, ore petrology, well cuttings, stratigraphic correlations, cements, environmental soil and dust, tissue and medical geology, and forensic geoscience.

Potential applications to other geologic studies can be significant: wherever information on fabric analysis, mineral composition, and mineral assemblages are of interest. In the very near future, automated mineralogy techniques will be applied across a wide spectrum of material sciences, and it is anticipated that as a result of this activity, students of mineralogy will be in even greater demand in the future.