OUR MISSION
To develop, organise & implement problem-driven, science-deep research & future-oriented education, contributing to the environmentally friendly production & recycling of metals, minerals & engineered materials, supporting (…) a climate-friendly, circular-economy. Read more >
News
Deep learning regression for quantitative LIBS analysis of aluminium scrap
The Life Cycle Engineering (LCE) research group (SIM2 – KU Leuven) developed a Deep Learning regression method for the quantitative analysis of aluminium post-consumer scrap using Laser Induced Breakdown Spectroscopy (LIBS). The work is published in Spectrochimica Acta Part B.
Cement and Concrete: From the Romans to Mars (Special Issue in Elements)
SIM² KU Leuven geologists Prof. Jan Elsen and Prof. Ruben Snellings are proud to announce the publication of the Elements Special Issue “Cement and Concrete: From the Romans to Mars”.
Classification of aluminium scrap by LIBS and RGB/D image fusion
KU Leuven’s LCE research group (SIM² KU Leuven) has demonstrated how data fusion of LIBS spectra and color (RGB) and Depth (D) images can improve the sorting of post-consumer aluminium scrap into commercially-interesting fractions.
Ben Gilliams: “Pyrometallurgy and hydrometallurgy are like yin and yang”
Following a 25-year VP-level career at Umicore, Ben Gilliams has decided to make a remarkable career switch. On January 9, Ben started as Senior Valorisation Director at SOLVOMET ISC, one of SIM² KU Leuven’s innovation flagships.
Meet our SIM² colleagues
Ben Gilliams: “Pyrometallurgy and hydrometallurgy are like yin and yang”
Following a 25-year VP-level career at Umicore, Ben Gilliams has decided to make a remarkable career switch. On January 9, Ben started as Senior Valorisation Director at SOLVOMET ISC, one of SIM² KU Leuven’s innovation flagships.
Understanding the origin of critical metals associated to hydrous magmas
With a background in igneous petrology and magmatic processes, Olivier Namur recently started as an Assistant Professor at SIM² KU Leuven. Find out about Olivier’s exciting research in this new SIM² interview.
Research Results
Deep learning regression for quantitative LIBS analysis of aluminium scrap
The Life Cycle Engineering (LCE) research group (SIM2 – KU Leuven) developed a Deep Learning regression method for the quantitative analysis of aluminium post-consumer scrap using Laser Induced Breakdown Spectroscopy (LIBS). The work is published in Spectrochimica Acta Part B.
Classification of aluminium scrap by LIBS and RGB/D image fusion
KU Leuven’s LCE research group (SIM² KU Leuven) has demonstrated how data fusion of LIBS spectra and color (RGB) and Depth (D) images can improve the sorting of post-consumer aluminium scrap into commercially-interesting fractions.
