Multi-dimensional characterisation of disperse systems in the context of Engineered Artificial Minerals (EnAM)

Urs Peuker, TU Bergakademie Freiberg, Germany

Metallurgical processes with primary as well as secondary raw material sourcing produce slags as byproducts. The main metallurgical function of the slag is taking up all chemical elements, which are undesired in the metal phase. Therefore, especially in secondary metallurgy, several critical and valuable elements end up in the slag phase, in a quite dissipated state. The EnAM-concept is a tool to recover those dissipated elements by concentrating them in a first step. Engineered Artificial Minerals (EnAM) are tailored mineral phases crystallized within a solidified slag matrix having a defined composition, particle size and shape. EnAM are the next step in slag engineering, since the mineral phase is engineered in its grain size and shape as well. Having reached a certain size and a certain morphology, EnAM-grains can be recovered with mechanical processes.
In crystallization grain size and shape are interconnected, therefore a holistic quantification of these two depended parameters becomes necessary. With the help of particle discrete data sets, which originate typically from imaging methods like SEM, SEM-EDX, dynamic imaging or X-ray tomography multi-dimensional particle property distributions can be set up. A particle discrete data-set can be seen as information vector for each individual particle, mineral grain respectively. This vector contains geometric information like different equivalent diameters, shape factors as well as information regarding composition, e.g. grey scale or EDX spectra. Based on this information it is possible to set up particle-property distributions, which thoroughly describe the disperse system, i.e. all EnAM-grains or EnAM-particles after mineral processing. It can be shown that the multi-dimensional representation is able to give a deep insight into the genesis and properties of EnAM.