Song, W.; von Appen, J.; Choi, P.; Dronskowski, R.; Raabe, D.; Bleck, W.: Atomic-scale investigation of epsilon and theta precipitates in bainite in 100Cr6 bearing steel by atom probe tomography and ab initio calculations. Acta Materialia 61 (20), pp. 7582 - 7590 (2013)
Li, Y.; Choi, P.-P.; Goto, S.; Borchers, C.; Raabe, D.; Kirchheim, R.: Atomic scale investigation of redistribution of alloying elements in pearlitic steel wires upon cold-drawing and annealing. Ultramicroscopy 132, pp. 233 - 238 (2013)
Marceau, R. K. W.; Choi, P.-P.: Understanding the detection of carbon in austenitic high-Mn steel using atom probe tomography. Ultramicroscopy 132, pp. 239 - 247 (2013)
Seol, J.-B.; Lee, B.-H.; Choi, P.; Lee, S.-G.; Park, C.-G.: Combined nano-SIMS/AFM/EBSD analysis and atom probe tomography, of carbon distribution in austenite/ε-martensite high-Mn steels. Ultramicroscopy 132, pp. 248 - 257 (2013)
Chen, Y. Z.; Herz, A.; Li, Y. J.; Borchers, C.; Choi, P.; Raabe, D.; Kirchheim, R.: Nanocrystalline Fe–C alloys produced by ball milling of iron and graphite. Acta Materialia 61 (9), pp. 3172 - 3185 (2013)
Sandim, M. J. R.; Tytko, D.; Kostka, A.; Choi, P.; Awaji, S.; Watanabe, K.; Raabe, D.: Grain boundary segregation in a bronze-route Nb3Sn superconducting wire studied by atom probe tomography. Superconductor Science and Technology 26, pp. 055008-1 - 055008-7 (2013)
Seol, J.-B.; Raabe, D.; Choi, P.; Park, H. S.; Kwak, J. H.; Park, C. G.: Direct evidence for the formation of ordered carbides in a ferrite based low-density Fe–Mn–Al–C alloy studied by transmission electron microscopy and atom probe tomography. Scripta Materialia 68 (6), pp. 348 - 353 (2013)
Cojocaru-Mirédin, O.; Choi, P.; Wuerz, R.; Raabe, D.: Exploring the p-n junction region in Cu(In,Ga)Se2 thin-film solar cells at the nanometer-scale. Applied Physics Letters 101 (18), pp. 181603-1 - 181603-5 (2012)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
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…
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…
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…
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…
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…