Nazarov, R.; Hickel, T.; Neugebauer, J.: First Principle Study on the Thermodynamics of Hydrogen in Iron and Steels. MRS Fall Meeting 2009 , Boston, MA, USA (2009)
Dick, A.; Hickel, T.; Neugebauer, J.: First principles calculation of stacking fault energies of FeMn-alloys. International Workshop on Ab initio Description of Iron and Steel (ADIS2008), Ringberg Castle, Germany (2008)
Udyansky, A.; Friák, M.; Grabowski, B.; Hickel, T.; Neugebauer, J.: First Principles Study of Fe–C interstitial solid solutions. International Workshop on Ab initio Description of Iron and Steel (ADIS2008), Ringberg Castle, Germany (2008)
Uijttewaal, M.; Hickel, T.; Neugebauer, J.: Phase transformations of Ni2MnGa shape memory alloy from first principles. International Workshop on Ab initio Description of Iron and Steel (ADIS2008), Ringberg Castle, Germany (2008)
Uijttewaal, M.; Hickel, T.; Neugebauer, J.: Ab initio investigation of temperature dependent effects in magnetic shape memory alloys. Evaluation of the SPP 1239 program, Dresden, Germany (2008)
Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: First principles determination of phase transitions: The (pre)martensitic transition in Ni2MnGa. UCSB-MPG Workshop on Inorganic Materials for Energy Conversion, Storage and Conservation, UCLA Lake Arrowhead Conference Center, CA, USA (2008)
Ismer, L.; Hickel, T.; Neugebauer, J.: First principles analysis of Hydrogen in Manganese-rich austentitic steels. Spring meeting of the German Physical Society (DPG), Berlin, Germany (2008)
Ismer, L.; Hickel, T.; Neugebauer, J.: First principles study of Hydrogen in Mn-rich austenitic steels. Spring meeting of the German Physical Society (DPG), Berlin, Germany (2008)
Körmann, F.; Dick, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Importance of magnetism for the thermal expansion of transition metals: An ab initio study. Spring meeting of the German Physical Society (DPG), Berlin, Germany (2008)
Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: A first principle determination of phase transitions in magnetic shape memory alloys. Multiscale approach to alloys: Advances and challenges, Stockholm, Sweden (2007)
Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: Determination of symmetry reduced structures by a soft-phonon analysis in magnetic shape memory alloys. Theory meets industry. The impact of density-functional calculation on materials science, Vienna, Austria (2007)
Grabowski, B.; Hickel, T.; Neugebauer, J.: Accuracy and error bars of DFT calculated thermodynamic properties for elementary metals. 13th International Workshop on Computational Physics and Materials Science: Total Energy and Force Methods, Trieste, Italy (2007)
Hickel, T.; Grabowski, B.; Uijttewaal, M.; Neugebauer, J.: Determination of symmetry-reduced structures by a soft-phonon analysis in magnetic shape memory alloys. 13th International Workshop on Computational Physics and Materials Science: Total Energy and Force Methods, Trieste, Italy (2007)
Hickel, T.; Grabowski, B.; Neugebauer, J.; Neumann, B.; Neumann, K.-U.; Ziebeck, K. R. A.: Temperature dependent properties of the Heusler alloy Ni2+xMn1-xGa. International Workshop on Ab initio Description of Iron and Steel (ADIS2006), Status and future challenges, Ringberg Castle, Germany (2006)
Hickel, T.; Nolting, W.: A self-consistent projection-operator approach to the Kondo-lattice model. The International Conference on Strongly Correlated Electron Systems, Vienna, Austria (2005)
Hickel, T.; Grabowski, B.; Neumann, K.; Neumann, K.-U.; Ziebeck, K. R. A.; Neugebauer, J.: Temperature dependent properties of Ni-rich Ni2MnGa. Materials Research Society fall meeting, Boston, MA, USA (2005)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.