Freysoldt, C.; Neugebauer, J.; Van de Walle, C. G.: Electrostatic interactions between charged defects in supercells. CECAM Workshop, Lausanne, Switzerland, June 08, 2009 - June 10, 2009. Physica Status Solidi B 248 (5), pp. 1067 - 1076 (2011)
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)
Freysoldt, C.: Exploring data-rich materials analytics with machine learning: how and why. Physikalisches Kolloquium, Universität Marburg, Marburg, Germany (2023)
Freysoldt, C.; Hickel, T.; Janßen, J.; Wang, N.; Zendegani, A.: High-throughput optimization of finite temperature phase stabilities: Concepts and application. Coffee with Max Planck, virtual seminar organized by the MPIE, Düsseldorf, Germany (2021)
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.
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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