Freysoldt, C.; Katnagallu, S.; Neugebauer, J.; Mishra, A.; Ashton, M. W.: Perspectives for machine learning applied to data-rich experiments on complex materials. Workshop on local probes of chemical bonding and atom probe tomography at RWTH Aachen, Aachen, Germany (2024)
Scientists at the Max Planck Institute for Sustainable Materials have developed a carbon-free, energy-saving method to extract nickel for batteries, magnets and stainless steel.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances