Neugebauer, J.: Ab initio Thermodynamik in der Materialwissenschaft: Status und Perspektiven. Fraunhofer Institut für Werkstoffmechanik Freiburg, Kolloquium, Freiburg, Germany (2007)
Hickel, T.; Grabowski, B.; Uijttewaal, M.; Neugebauer, J.: Ab initio determination of symmetry-reduced structures by a soft-phonon analysis in Ni_{2}MnGa. Spring meeting of the German Physical Society (DPG), Regensburg, Germany (2007)
Hickel, T.; Grabowski, B.; Uijttewaal, M.; Neugebauer, J.: Ab initio prediction of structural and thermodynamic properties of magnetic shape memory alloys. Focus meeting of the SPP 1239: Fundamentals of the Magnetic Shape Memory Effect: Materials properties & simulations, Schloss Ringberg, Germany (2007)
Marquardt, O.; Wahn, M.; Lymperakis, L.; Hickel, T.; Neugebauer, J.: Implementation and application of a multi-scale approach to electronic properties of group III-nitride based semiconductor nanostructures. Workshop on Nitride Based Nanostructures, Berlin, Germany (2007)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Ab initio prediction of structural and thermodynamic properties of metals. Seminar Abt. Jansen, MPI für Festkörperforschung, Stuttgart, Germany (2007)
Marquardt, O.; Hickel, T.; Neugebauer, J.: A k.p approach to electronic states and Coulomb interaction in semiconductor quantum dots. Forschergruppentreffen Uni Bremen, Bremen, Germany (2007)
Grabowski, B.; Hickel, T.; Neugebauer, J.: From ab initio to materials properties: Accuracy and error bars of DFT thermodynamics. MMM Workshop, Barcelona, Spain (2007)
Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: Ab initio prediction of structural and thermodynamic properties of metals. International Max-Planck Workshop on Multiscale Materials Modeling of Condensed Matter, Sant Feliu de Guixols, Spain (2007)
Friák, M.; Neugebauer, J.: Anomalous equilibrium volume change of magnetic Fe–Al crystals. Materials Research Society fall meeting, Boston, MA, USA (2006)
Raabe, D.; Sander, B.; Friák, M.; Neugebauer, J.: Bottom up design of novel Titanium-based biomaterials through the combination of ab-initio simulations and experimental methods. Materials Research Society fall meeting, Boston, MA, USA (2006)
Abu-Farsakh, H.; Neugebauer, J.: Tailoring the N-solubility in InGaAs-alloys by surface engineering: Applications and limits. 1. Harzer Ab initio Workshop, Clausthal, Germany (2006)
Ismer, L.; Ireta, J.; Neugebauer, J.: Vibrational modes and thermodynamic properties of the secondary structure of proteins. 1. Harzer Ab initio Workshop, Clausthal (2006)
Neugebauer, J.; Wahn, M.: Exact exchange within Kohn-Sham formalism. Standard and variational approach. 1. Harzer Ab initio Workshop, Clausthal-Zellerfeld (2006)
Hickel, T.; Neugebauer, J.: Ab initio description of grain boundaries and diffusion processes. Arbeitstreffen der Helmholtz-Allianz „HYPER“,, Darmstadt (2006)
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.