Technology
In terms of underpinning technology, it is a Scanning Electron Microscope (SEM)-based automated image analyzer, based on FEI’s Quanta platform, and fitted with dual, liquid nitrogen-free (SDD-type) EDS detectors. It is available as either a Tungsten filament (MLA 650, MLA 250) or Field Emission Gun (FEG) source system (MLA 650F).
Capability
It is a product of record and considered to be one of the most advanced automated analyzers available for minerals, rocks and man-made materials. MLA uses combinations of Backscattered Electron Intensity and rapidly acquired Electron Induced Secondary X-Ray spectra as the primary methods of mineral identification. It offers expert-level, petrographic-based, image analysis functionality (e.g. grain size, grain shape analysis, liberation analysis etc.). The large sample chamber can accommodate up to 14 samples (30mm diameter) at one time. Sample preparation for the MLA requires that the material to be analyzed is presented to the instrument as a flat, carbon coated surface. The solution has fully customizable measurement modes.
Unique features
History - The MLA was developed by the University of Queensland’s JKMRC and JKTech in the late 1990’s, commercialized in 2000, and acquired by FEI in 2009.
Mineral Identification - MLA automatically identifies minerals and phases under the electron beam by using an EDS X-ray spectral pattern matching algorithm, by comparing the x-ray spectrum to a library of reference spectra.
Proprietary Image Analysis Software - MLA uses DataView image analysis software to analyze the resulting data.
Detector Options - MLA is available with both Bruker and EDAX EDS systems.
Main Applications
MLA is a product of record for the mining and mineral processing industry, but has recently found acceptance within the broader geosciences community, where it is used to quantify ore textures in, for example, cm-scale unbroken drill core samples. The resulting images and accompanying data are used to provide input to predictive geometallurgical programs, as well as provide insights into petrogenetic modelling of ore body evolution.