Contact

Department of Exploration
Dr. Richard Gloaguen

Department of Analytics
Prof. Dr. Jens Gutzmer
Dr. Axel Renno

3D Computer-Tomography

Foto: 3D image of a REE (red) bearing carbonate rock ©Copyright: Dr. Jose Ricardo da Assuncao Godinho

3D image of rare earth minerals (red) in a carbonate rock

Source: Dr. da Assuncao Godinho, Jose Ricardo

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 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 photon counting X-ray detector the CT can also yield chemical information in 3D. 

By applying machine learning approaches to this multi-layered data set, we develop automated workflows and are able to link raw material data to process simulation software.

To plan a CT experiment with our scanner, please use the following interactive user interface: https://ctplanning-prototype-v1p4.streamlit.app/