Qin, Y.; Li, J.; Herbig, M.: Microstructural origin of the outstanding durability of the high nitrogen bearing steel X30CrMoN15-1. Materials Characterization 159, 110049 (2020)
Srikakulapu, K.; Qin, Y.; Sreekala, L.; Morsdorf, L.; Herbig, M.: On the decomposition resistance of carbonitride precipitates during high-pressure torsion in X30CrMoN15-1 bearing steel. High Nitrogen Steel conference, HNS 2021, online, Shanghai, China (2021)
Qin, Y.; Mayweg, D.; Tung, P.-Y.; Pippan, R.; Herbig, M.: Mechanism of cementite decomposition in 100Cr6 bearing steels during high pressure torsion. MSE Congress 2020, virtual, Sankt Augustin, Germany (2020)
Qin, Y.: Effect of post-heat treatment on the microstructure and mechanical properties of SLM-produced IN738LC. Master, RWTH Aachen, Aachen, Germany (2017)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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