Mayweg, D.; Morsdorf, L.; Wu, X.; Herbig, M.: The role of carbon in the white etching crack phenomenon in bearing steels. Acta Materialia 203, 116480 (2021)
Tung, P.-Y.; McEniry, E.; Herbig, M.: The role of electric current in the formation of white-etching-cracks. Philosophical Magazine 101 (1), pp. 59 - 76 (2021)
Morsdorf, L.; Mayweg, D.; Li, Y.; Diederichs, A.; Raabe, D.; Herbig, M.: Moving cracks form white etching areas during rolling contact fatigue in bearings. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 771, 138659 (2020)
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)
Kumar, A.; Dutta, A.; Makineni, S. K.; Herbig, M.; Petrov, R.; Sietsma, J.: In-situ observation of strain partitioning and damage development in continuously cooled carbide-free bainitic steels using micro digital image correlation. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 757, pp. 107 - 116 (2019)
Kühbach, M.; Breen, A. J.; Herbig, M.; Gault, B.: Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim. Microscopy and Microanalysis 25 (2), pp. 320 - 330 (2019)
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
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…