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)
Hickel, T.; Neugebauer, J.: Ab initio description of grain boundaries and diffusion processes. Arbeitstreffen der Helmholtz-Allianz „HYPER“,, Darmstadt (2006)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Temperature dependent properites of Ni2MnGa – An ab initio approach -. European Symposium on Martensitic Transformations (ESOMAT), Bochum (2006)
Hickel, T.: Ab initio description of Iron and Steel - The department of computational materials design -. Visit of ISIT at MPIE, MPIE, Düsseldorf (2006)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Ferromagnetic shape memory alloys: Thermodynamic and magnetic properites. Joint group meeting at Material Research Laboratory of University of California, Santa Barbara, Santa Barbara, USA (2006)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Temperature and magnetic field dependent properites of Ni2MnGa. Kolloquium zur Festkörpertheorie, Institut für Physik der Humboldt-Universtität zu Berlin, Berlin, Germany (2006)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Temperature and magnetic field dependent properites of Ni2MnGa. DPG Spring Meeting of the Division Condensed Matter, Dresden, Germany (2006)
Hickel, T.; Grabowski, B.; Neugebauer, J.: Temperature dependent properites of Shape-memory alloys. Physics Seminar of Loughborough University, Loughborough, UK (2006)
Hickel, T.; Neugebauer, J.: Temperature-dependent ab initio investigation of the martensitic phase transition in magnetic SMAs. Kickoff-Workshop of SPP1239, Dresden, Germany (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
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.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
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…