Lai, M.; Li, T.; Yan, F.; Li, J.; Raabe, D.: Revisiting o phase embrittlement in metastable b titanium alloys: Role of elemental partitioning. Scripta Materialia 193, pp. 38 - 42 (2021)
Lai, M.; Li, Y.; Lillpopp, L.; Ponge, D.; Will, S.; Raabe, D.: On the origin of the improvement of shape memory effect by precipitating VC in Fe–Mn–Si-based shape memory alloys. Acta Materialia 155, pp. 222 - 235 (2018)
Lai, M.; Li, T.; Raabe, D.: ω phase acts as a switch between dislocation channeling and joint twinning- and transformation-induced plasticity in a metastable β titanium alloy. Acta Materialia 151, pp. 67 - 77 (2018)
Zhang, J.; Tasan, C. C.; Lai, M.; Yan, D.; Raabe, D.: Partial recrystallization of gum metal to achieve enhanced strength and ductility. Acta Materialia 135, pp. 400 - 410 (2017)
Zhang, J.; Tasan, C. C.; Lai, M.; Zhang, J.; Raabe, D.: Damage resistance in gum metal through cold work-induced microstructural heterogeneity. Journal of Materials Science 50 (17), pp. 5694 - 5708 (2015)
Zhang, J.; Tasan, C. C.; Lai, M.; Zhang, J.; Raabe, D.: Damage Resistance through Hierarchical Microstructure Development on GUM Metal. Materials Science and Engineering (MSE2014), Darmstadt, Germany (2014)
Zhang, J.; Tasan, C. C.; Lai, M.; Springer, H.; Raabe, D.: Microstructural and Mechanical Characterization of Cold Work Effects in GUM Metal. 9th International Conference on Advances in Experimental Mechanics, Cardiff, UK (2013)
Zhang, J.; Raabe, D.; Lai, M.; Yan, D.; Tasan, C. C.: Site-preferential recrystallization and nano-precipitation to achieve improved mechanical properties. MRS Fall Meeting 2016, Boston, MA, USA (2016)
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.