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)
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)
Aota, L. S.; Souza Filho, I. R.; Roscher, M.; Ponge, D.; Sandim, H. R. Z.: Strain hardening engineering via grain size control in laser powder-bed fusion. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 838, 142773 (2022)
Wang, X.; Liu, C.; Sun, B.; Ponge, D.; Jiang, C.; Raabe, D.: The dual role of martensitic transformation in fatigue crack growth. Proceedings of the National Academy of Sciences of the United States of America 119 (9), e2110139119 (2022)
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
This project will aim at developing MEMS based nanoforce sensors with capacitive sensing capabilities. The nanoforce sensors will be further incorporated with in situ SEM and TEM small scale testing systems, for allowing simultaneous visualization of the deformation process during mechanical tests
The utilization of Kelvin Probe (KP) techniques for spatially resolved high sensitivity measurement of hydrogen has been a major break-through for our work on hydrogen in materials. A relatively straight forward approach was hydrogen mapping for supporting research on hydrogen embrittlement that was successfully applied on different materials, and…
It is very challenging to simulate electron-transfer reactions under potential control within high-level electronic structure theory, e. g. to study electrochemical and electrocatalytic reaction mechanisms. We develop a novel method to sample the canonical NVTΦ or NpTΦ ensemble at constant electrode potential in ab initio molecular dynamics…
Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO2-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into…
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
The field of micromechanics has seen a large progress in the past two decades, enabled by the development of instrumented nanoindentation. Consequently, diverse methodologies have been tested to extract fundamental properties of materials related to their plastic and elastic behaviour and fracture toughness. Established experimental protocols are…
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…