Rao, Z.; Bajpai, A.; Zhang, H.: Active learning strategies for the design of sustainable alloys. Philosophical Transactions of the Royal Society A 382 (2284), 20230242 (2024)
Rao, Z.; Li, Y.; Zhang, H.; Colnaghi, T.; Marek, A.; Rampp, M.; Gault, B.: Direct recognition of crystal structures via three-dimensional convolutional neural networks with high accuracy and tolerance to random displacements and missing atoms. Scripta Materialia 234, 115542 (2023)
Pyczak, F.; Liang, Z.; Neumeier, S.; Rao, Z.: Stability and Physical Properties of the L12-γ' Phase in the CoNiAlTi-System. Metallurgical and Materials Transactions A 54 (5), pp. 1661 - 1670 (2023)
Zhu, Z.; Ng, F. L.; Seet, H. L.; Lu, W.; Liebscher, C.; Rao, Z.; Raabe, D.; Nai, S. M. L.: Superior mechanical properties of a selective-laser-melted AlZnMgCuScZr alloy enabled by a tunable hierarchical microstructure and dual-nanoprecipitation. Materials Today 52, pp. 90 - 101 (2022)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.