Niendorf, T.; Wegener, T.; Li, Z.; Raabe, D.: On the fatigue behavior of dual-phase high-entropy alloys in the low-cycle fatigue regime. Fatique 2018, Poitiers, France (2018)
Li, Z.; Raabe, D.: Tuning Phase Transformation in Compositionally Complex Alloys for Superior Mechanical Properties. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Oh, H. S.; Li, Z.; Kim, J. Y.; Ryu, C. W.; Meyer, A.; Tsuchiya, K.; Raabe, D.; Park, E. S.: Phase Stabilization of High Entropy Alloy under Dynamic Forcing Condition. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Li, Z.; Raabe, D.: Designing novel high-entropy alloys towards superior properties. Frontiers in Materials Processing Applications, Research and Technology (FiMPART'2017), Bordeaux, France (2017)
Li, Z.: Designing and understanding novel high-entropy alloys towards superior properties. Talk at Universität Kassel, Institut für Werkstofftechnik, Kassel, Germany (2017)
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
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…