Grabowski, B.; Glensk, A.; Korbmacher, D.; Huang, L.; Körmann, F.; Hickel, T.; Neugebauer, J.: First principles at finite temperatures: New approaches and massively parallel computations. CMSI International Symposium 2013: Extending the power of computational materials sciences with K-computer, Ito International Research Center, University of Tokyo, Japan (2013)
Hickel, T.; Nazarov, R.; Neugebauer, J.: Aspekte der Wasserstoffversprödung von Stählen: Verständnisgewinn durch quantenmechanische Simulationen. AKE Workshop, DECHEMA, Frankfurt a. M, Germany (2013)
Dey, P.; Nazarov, R.; Friák, M.; Hickel, T.; Neugebauer, J.: kappa-carbides as precipitates in austenitic steels: Ab initio study of structural, magnetic and Interface properties. EUROMAT 2013, Sevilla, Spain (2013)
Neugebauer, J.: Ab initio based multiscale modeling of structural materials: From a predictive thermodynamic description to tailored mechanical properties. CECAM Conference, Platja d’Aro, Spain (2013)
Dutta, B.; Körmann, F.; Dey, P.; Hickel, T.; Neugebauer, J.: Ab-initio based prediction of chemical trends for phase transitions in magnetic shape memory alloys. Weekly Seminar, Interdisciplinary Centre for Advanced Materials Simulation (ICAMS), Ruhr-Universität Bochum, Bochum, Germany (2013)
Lymperakis, L.; Weidlich, P. H.; Eisele, H.; Schnedler, M.; Nys, J.-P.; Grandidier, B.; Stievenard, D.; Dunin-Borkowski, R.; Neugebauer, J.; Ebert, P.: Revealing Hidden Surface States of Non-Polar GaN Facets by an Ab Initio Tailored STM Approach. 10th International Conference on Nitride Semiconductors, Washigton DC, USA (2013)
Dutta, B.; Hickel, T.; Neugebauer, J.: Ab-initio based prediction of chemical trends in magnetic shape memory alloys. Mini Workshop on Lattice Dynamics, Uppsala University, Uppsala, Sweden (2013)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Modelling Mica from first-principles. 1st Dutch/German Workshop on Computational Materials Design, Balk, The Netherlands (2013)
Dutta, B.; Hickel, T.; Neugebauer, J.: Phase transitions in magnetic shape memory alloys: Ab-initio based prediction of chemical trends. Fourth International Conference on Ferromagnetic Shape Memory Alloys (ICFSMA'13), Boise, ID, USA (2013)
Ilhan, M.; Todorova, M.; Neugebauer, J.: Adsorption of H, S, and O on the Iron (100) surface. 1st Dutch/German Workshop on Computational Materials Design, Balk, The Netherlands (2013)
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…