3D Computer-Tomography
3D image of a REE (red) bearing carbonate rock
Most well established high resolution characterization techniques are limited to 2-dimensional data, despite the fact that raw materials are inherently 3-dimensional objects. The purpose of developing novel 3D characterization techniques is to enable a more reliable resource characterization(2) and prediction of material behavior which ultimately allows for an unprecedented optimization of resource recovery and energy efficiency.
To develop such breakthrough approaches, we merge quantitative 2-dimensional data from scanning electron microscopy (SEM) with 3-dimensional data from computed X-ray tomography (or CT for short). SEM-based image analysis tools are standard in resource characterization, providing chemical information (for example mineral distribution) and textural parameters (for example particle size or mineral association). CT, on the other hand, adds the 3D-spatial dimension. Combined with an energy dispersive X-ray detector the CT can also yield chemical information in 3D.
By applying machine learning approaches(3) to this multi-layered data set, we develop automated workflows and are able to link raw material data to process simulation software.
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https://www.hzdr.de/db/Cms?pOid=71388
