Li, J.; Pharr, G. M.; Kirchlechner, C.: Quantitative insights into the dislocation source behavior of twin boundaries suggest a new dislocation source mechanism. Journal of Materials Research 36 (10), pp. 2037 - 2046 (2021)
Luo, W.; Kirchlechner, C.; Li, J.; Dehm, G.; Stein, F.: Composition dependence of hardness and elastic modulus of the cubic and hexagonal NbCo2 Laves phase polytypes studied by nanoindentation. Journal of Materials Research 35 (2), pp. 185 - 195 (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)
Li, J.; Dehm, G.; Kirchlechner, C.: Dislocation source activation by nanoindentation in single crystals and at grain boundaries. E-MRS Spring, Strasbourg, France (2018)
Li, J.; Dehm, G.; Kirchlechner, C.: Differences in dislocation source activation stress in the grain interior and at twin boundaries using nanoindentation. Nanobruecken 2018, Erlangen, Germany (2018)
Li, J.; Dehm, G.; Kirchlechner, C.: Grain Boundaries acting as dislocation sources. Gordon Research Seminar "Thin Film & Small Scale Mechanical Behavior", Lewiston, ME, USA (2018)
Li, J.: Probing dislocation nucleation in grains and at Ʃ3 twin boundaries of Cu alloys by nanoindentation. Dissertation, Ruhr-Universität Bochum (2020)
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…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…