Hickel, T.; Zendegani, A.; Körmann, F.; Neugebauer, J.: Energetics of non-stoichiometric stacking faults in Fe–Nb alloys: An ab initio study. TMS 2019 Annual Meeting, San Antonio, TX, USA (2019)
Neugebauer, J.; Janßen, J.; Körmann, F.; Hickel, T.; Grabowski, B.: Exploration of large ab initio data spaces to design materials with superior mechanical properties. Physics and Theoretical Division Colloquium, Los Alamos, NM, USA (2019)
Ikeda, Y.; Körmann, F.; Neugebauer, J.: Impact of chemical compositions and interstitial alloying on the stacking fault energy of CrMnFeCoNi-based HEAs from first principles. The 2nd International Conference on High-Entropy Materials , Jeju, South Korea (2018)
Dutta, B.; Körmann, F.; Hickel, T.; Neugebauer, J.: Temperature-driven effects in functional materials: Ab initio insights. Talk at University Pierre and Marie CURIE (UPMC), Paris, France (2017)
Zendegani, A.; Körmann, F.; Hickel, T.; Hallstedt, B.; Neugebauer, J.: Thermodynamic properties of the quaternary Q phase in Al–Cu–Mg–Si: a combined ab-initio, phonon and compound energy formalism approach. International Conference on Advanced Materials Modelling (ICAMM), Rennes, France (2016)
Körmann, F.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Lattice excitations in magnetic alloys: Recent advances in ab initio modeling of coupled spin and atomic fluctuations. TMS Annual Meeting 2016, Nashville, TN, USA (2016)
Körmann, F.: Temperature dependent coupling of atomic and magnetic degrees of freedom from first-principles. Workshop on Electronic Structure Theory of Accelerated Design of Structural Materials, Moscow, Russia (2015)
Körmann, F.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Temperature-dependent coupling of atomic and magnetic degree of freedom from first-principles. Electronic Structure Theory for the Accelerated Design of Structural Materials, Moscow, Russia (2015)
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.