Meeting the growing need in Critical Raw Materials (CRM) is one of the greatest challenges for the next decades in EU and beyond. Highly flexible, rapid and reliable measurement techniques are needed to enhance our capacity of pollutant-free CRM exploration, exploitation and recycling in various environments.
LIBS-SCReeN will be devoted to the optimization and application of Laser-induced break-down Spectroscopy (LIBS) techniques for multiscale detection and characterization of Critical Raw Materials (CRM), with emphasis on the Belgian lead-zinc deposits. This type of mineralization is known worldwide to potentially host germanium, gallium, indium and cadmium. In Belgium we know the potential for germanium. Conversely, mining and processing activities linked to Pb and Zn can contaminate the environment. Cd is a major contaminant of soils in Belgium.
The large number of spectral data generated with LIBS on reference samples with known mineralogical and chemical characteristics will feed one of the research cornerstones of this project: the application of artificial intelligence, especially application-oriented deep-learning chemometrics to automatize treatment of LIBS data streams. The performance of basics methodologies in machine learning (ML) and pattern recognition will be assessed.
Moreover, the project will strengthen Belgium’s expertise in LIBS, which is currently dispersed among federal institutions and universities. Creating a Belgian LIBS research cluster will be of added value.
