Saksena, A.; Sun, B.; Dong, X.; Khanchandani, H.; Ponge, D.; Gault, B.: Optimizing site-specific specimen preparation for atom probe tomography by using hydrogen for visualizing radiation-induced damage. International Journal of Hydrogen Energy 50 (Part A), pp. 165 - 174 (2024)
Elkot, M.; Sun, B.; Zhou, X.; Ponge, D.; Raabe, D.: On the formation and growth of grain boundary k-carbides in austenitic high-Mn lightweight steels. Materials Research Letters 12 (1), pp. 10 - 16 (2024)
Shi, H.; Nandy, S.; Cheng, H.; Sun, B.; Ponge, D.: In-situ investigation of the interaction between hydrogen and stacking faults in a bulk austenitic steel. Acta Materialia 262, 119441 (2024)
Sukumar Prithiv, T.; Gault, B.; Li, Y.; Andersen, D.; Valle, N.; Eswara, S.; Ponge, D.; Raabe, D.: Austenite grain boundary segregation and precipitation of boron in low-C steels and their role on the heterogeneous nucleation of ferrite. Acta Materialia 252, 118947 (2023)
Narasimha Sasidhar, K.; Zhou, X.; Rohwerder, M.; Ponge, D.: On the phase transformation pathway during localized grain boundary oxidation in an Fe-10 at% Cr alloy at 200°C. Corrosion Science 214, 111016 (2023)
Varanasi, R. S.; Gault, B.; Ponge, D.: Effect of Nb micro-alloying on austenite nucleation and growth in a medium manganese steel during intercritical annealing. Acta Materialia 229, 117786 (2022)
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
In this project, we employ atomistic computer simulations to study grain boundaries. Primarily, molecular dynamics simulations are used to explore their energetics and mobility in Cu- and Al-based systems in close collaboration with experimental works in the GB-CORRELATE project.
This project is a joint project of the De Magnete group and the Atom Probe Tomography group, and was initiated by MPIE’s participation in the CRC TR 270 HOMMAGE. We also benefit from additional collaborations with the “Machine-learning based data extraction from APT” project and the Defect Chemistry and Spectroscopy group.