Elstnerová, P.; Friák, M.; Šob, M.; Neugebauer, J.: Prediction of the Ground State of NiN and Ni2N within the Quantum Mechanical Study. Multiscale Design of Advanced Materials, Brno, Czech Republic (2011)
Hickel, T.; Glensk, A.; Grabowski, B.; Neugebauer, J.: Ab initio up to the melting point: Integrated approach to derive accurate thermodynamic data for Al alloys. European Aluminium Association, European Aluminium Technology Platform, Working Group 5: Predictive Modelling, 5th workshop: ab initio modelling, Aachen, Germany (2011)
Hickel, T.; Al-Zubi, A.; Neugebauer, J.: Ab initio based prediction of phase diagrams: Application to magnetic shape-memory alloys. 9. Materialwissenschaftlicher Tag der Ruhr-Universtät Bochum, Bochum, Germany (2011)
Neugebauer, J.: Fully ab initio determination of free energies: Methodological challenges and applications. Conference on Computational Physics (CCP2011), Gatlinburg, TN, USA (2011)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: The dangling-bond defect in amorphous silicon: Insights from theoretical calculations of the EPR parameters. Workshop on Advanced EPR for material and solar energy research, Berlin, Germany (2011)
Izanlou, A.; Todorova, M.; Friák, M.; Palm, M.; Neugebauer, J.: Theoretical study of the environmental effect of H-containing gases on Fe–Al surfaces. FeAl2011, Discussion Meeting on the Development of Innovative Iron Aluminium Alloys, Lanzarote, Canary Islands, Spain (2011)
Neugebauer, J.: Doping and growth issues in group-III nitrides: An ab initio perspective. Workshop on III-Nitrides Growth, Characterization and Simulation, Berlin, Germany (2011)
Neugebauer, J.: Ab initio guided materials characterization and design. Science Vision for the European Spallation Source, Bad Reichenhall, Germany (2011)
Elstnerová, P.; Friák, M.; Neugebauer, J.: Enhancing mechanical properties of calcite by Mg substitutions - A Quantum-Mechanical Study. 12th International Symposium on Physics of Materials, Prague, Czech Republic (2011)
Neugebauer, J.: Ab initio based modeling of structural materials with superior properties: From a predictive thermodynamic description to tailored mechanical properties. EUROMAT 2011, Montpellier, France (2011)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: The Dangling-Bond Defect in Amorphous Silicon: Statistical Random Versus Kinetically Driven Defect Geometries. 24th International Conference on Amorphous and Nanocrystalline Semiconductors (ICANS 24), Nara, Japan (2011)
Gutierrez-Urrutia, I.; Dick, A.; Hickel, T.; Neugebauer, J.; Raabe, D.: Understanding TWIP steel microstructures by using advanced electron microscopy and ab initio predictions. International Conference on Processing & Manufacturing of Advanced Materials THERMEC 2011, Québec City, QC, Canada (2011)
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
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…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.