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)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
Hydrogen in aluminium can cause embrittlement and critical failure. However, the behaviour of hydrogen in aluminium was not yet understood. Scientists at the Max-Planck-Institut für Eisenforschung were able to locate hydrogen inside aluminium’s microstructure and designed strategies to trap the hydrogen atoms inside the microstructure. This can…
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…