Wang, N.; Freysoldt, C.; Zhang, S.; Liebscher, C.; Neugebauer, J.: Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors. Microscopy and Microanalysis 27 (6), pp. 1454 - 1464 (2021)
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)
Hickel, T.; Freysoldt, C.; 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)
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
Developing and providing accurate simulation techniques to explore and predict structural properties and chemical reactions at electrified surfaces and interfaces is critical to surmount materials-related challenges in the context of sustainability, energy conversion and storage. The groups of C. Freysoldt, M. Todorova and S. Wippermann develop…