Automated materials characterization
Automated materials characterization is performed on a wide range of natural and artificial materials. We analyze raw material samples by both MLA (Mineral Liberation Analyzer) and QEMSCAN (Quantitative Evaluation of Minerals by Scanning Electron Microscopy). These techniques allow us to determine many decisive material parameters, including the abundance of key minerals, metal deportment, and the association and liberation of specific mineral grains. Furthermore, the measurement of up to 20,000 particles per sample and of detailed mineral maps, as well as the development of project-specific databases, enable us to deliver valuable data for the improvement of processes and exploration strategies.
Automated materials characterization (automated mineralogy) of ores enables the determination of modal abundance, mineral associations and intergrowths as well as elemental distribution (metal deportment). Additionally, parameters relevant for developing the most efficient beneficiation routes are determined, including particle or grain size, mineral liberation and theoretical metal recovery (grade/recovery curves). By applying special search modes minerals or metals of interest, e.g. gold, silver and platinum group metals can be traced.
Processing products (concentrates, intermediates, tailings)
The detailed characterization of processing products via MLA and QEMSCAN significantly contributes to plant optimization. Analyzing processing products allows to determine key parameters such as particle size, particle density distribution, mineral grain size, mineral liberation, phase specific surface area (PSSA) as well as theoretical elemental grade/recovery and theoretical mineral grade/recovery. Material losses can be traced and thus reduced.
Automated materials characterization enables the evaluation of comminution and separation processes during recycling. The accumulation of specific phases in certain processing steps and size fractions can be detected and therefore used for process optimization.
Environmentally relevant materials (e.g., tailings, re-mining)
Today, automated materials characterization techniques are applied to environmental rehabilitation and re-mining. MLA and QEMSCAN analyses can be used to characterize tailings material with regard to potential pollutants and valuable residuals. The recognition of environmentally relevant mineral associations, e.g. containing penalty elements, is of particular importance.
Automated materials characterization is used to detect and identify compositional impurities in special glasses with high purity requirements.
In the ceramic industry, the material characterization is used for quality control. Both the material structures (e.g. in respect of agglomerate formation) as well as intergrowths of phases are evaluated to ensure high quality products.
Metals and alloys
The automated material characterization of metals and alloys is in particular suitable for quality control and for the detection and identification of critical impurities.
The automated material characterization of semiconductor materials is used for quality control and for the detection and identification of critical impurities.
In the application field of building materials, both the feed materials and the final products can be analyzed. The applications are the exact material characterization for quality control as well as for detection and identification of critical impurities.
Rocks and sediments
ERZLABOR analyzes solid as well as granular materials. All three rock groups, magmatic, metamorphic as well as sedimentary rocks are analyzed with regard to their quantitative mineralogy. Furthermore, minor and trace minerals are identified and mapped.
One of the very first applications of automated materials characterization in the early 1970s was the phase identification and determination of extraterrestrial matter.