Automated analysis

Geochemical modeling of geological events is based on knowledge of mineralogy and bulk chemistry of the rocks that recorded the alteration. Using standards-based EDS analysis, ZEISS Mineralogic 2D provides precise, actionable bulk chemistry, mineralogy, and phase chemical zonation at the micron scale in a single analysis. This reduces the time to results and the volume of corroborating data that must be acquired. Return to grains of interest with the press of a single button to acquire trace element profiles using WDS or export the coordinate map for use with TOF-SIMS and LA-ICP-MS. For maximum accuracy, use the highly sensitive standards-based quantitative EDS. For the fastest analysis speeds, choose BSD greyscale alone. Include element ratio rules to discriminate end members of a solid solution. High-resolution imaging combined with a full suite of image processing functions gives you a powerful edge to solve previously impossible application challenges.

Geological studies often involve complex, heterogeneous systems, and therefore simple classification criteria may not be sufficient to fully describe a system. Use morphological parameters with mineral chemistry to further describe your mineralogy and differentiate key evidence. Classify lithology to automatically categorize your particles, identify and quantify ore types, and describe mineral texture by combining chemical and morphochemical classifications. Combine chemistry with grain size, shape parameters, grey level, and porosity to achieve in-line morpho chemical quantification with all the results tabulated immediately at the end of the analysis. Distinguish between crystalline and porous instances of your pyrite or goethite to better assess mineral genesis, instances of bio-mineralization, and/or make fact-based operational decisions.

The phrase "automated mineralogy" has been synonymous with the use of scanning electron microscopes (SEM) for decades. The classification of minerals using SEM-based energy dispersive spectroscopy (EDS) chemical measurements has been the only method for rapid, automated phase ID in microscopy.

Making full use of the imaging capability of the X-ray microscope, enhanced by DeepRecon noise-reducing deep learning algorithms, Mineralogic 3D automatically classifies the mineralogy of the sample based on attenuation measurements. The ability to classify the mineralogy in tomographic scans is unique and when combined with the morphological measurements of the 3D reconstructed entities allows the calculation of standard and customized data outputs such as true grain size/shape and mineral association measurements.

Where 2D automated mineralogy offers liberation based on exposed surfaces or edges, associations based on linear contacts, and modal mineralogy based on phases exposed on the surface of the sample mount, 3D mineralogy measures liberation based on the volume of the grains and their exposure on the surface of the unaltered particle. Associations are based on full mineral surface contacts with other phases, and modal mineralogy accounts for all grains: those exposed on the surface of the particles and those obscured within.

ZEISS Mineralogic 3D applies X-ray microscopy techniques and deep learning algorithms to execute automated mineralogy analyses in 3D that provide particle identification, mineral classification, and data outputs, including liberation and association measurements.