Duarte, M. J.; Fang, X.; Rao, J.; Krieger, W.; Brinckmann, S.; Dehm, G.: In situ nanoindentation during electrochemical hydrogen charging: a comparison between front-side and a novel back-side charging approach. Journal of Materials Science 56 (14), pp. 8732 - 8744 (2021)
Luo, W.; Kirchlechner, C.; Fang, X.; Brinckmann, S.; Dehm, G.; Stein, F.: Influence of composition and crystal structure on the fracture toughness of NbCo2 Laves phase studied by micro-cantilever bending tests. Materials and Design 145, pp. 116 - 121 (2018)
Li, Y.; Fang, X.; Zhang, S.; Feng, X.: Microstructure evolution of FeNiCr alloy induced by stress-oxidation coupling using high temperature nanoindentation. Corrosion Science 135, pp. 192 - 196 (2018)
Yue, M.; Dong, X.; Fang, X.; Feng, X.: Effect of interface reaction and diffusion on stress-oxidation coupling at high temperature. Journal of Applied Physics 123 (15), 155301 (2018)
Fang, X.; Dong, X.; Jiang, D.; Feng, X.: Modification of the mechanism for stress-aided grain boundary oxidation ahead of cracks. Oxidation of Metals 89 (3-4), pp. 331 - 338 (2018)
Lu, S.-Y.; Chen, Y.; Fang, X.; Feng, X.: Hydrogen peroxide sensor based on electrodeposited Prussian blue film. Journal of Applied Electrochemistry 47 (11), pp. 1261 - 1271 (2017)
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…