Dick, A.; Körmann, F.; Hickel, T.; Neugebauer, J.: Thermodynamic properties of cementite including magnetic, vibronic, and electronic excitations from ab initio. TMS Annual meeting 2012, Orlando, FL, USA (2012)
Hickel, T.: Advancing ab initio methods to finite temperatures: The opening of new routes in materials design. Physikalisches Kolloquium der Ruhr-Universität Bochum, Bochum, Germany (2012)
Hickel, T.; Sandschneider, N.; Friák, M.; Neugebauer, J.; Ouyang, Y.: Ab initio determination of point defects and derived diffusion properties in metals. TMS Annual meeting 2012, Orlando, FL, USA (2012)
Liot, F.; Friák, M.; Hickel, T.; Neugebauer, J.: The influence of ternary additions in the Fe2Nb C14 Laves phase. ICAMS Advanced Discussions, Bochum, Germany (2012)
Palumbo, M.; Fries, S. G.; Hammerschmidt, T.; Drautz, R.; Körmann, F.; Hickel, T.; Neugebauer, J.: SAPIENS, a DFT and experimental based thermophysical database for pure elements. DPG Frühjahrstagung 2012, Berlin, Germany (2012)
Grabowski, B.; Söderlind, P.; Hickel, T.; Neugebauer, J.: Ab Initio Thermodynamics of the fcc-bcc Transition in Ca Including All Relevant FiniteTemperature Excitation Mechanisms. TMS 2012, Orlando, FL, USA (2012)
Nazarov, R.; Hickel, T.; Neugebauer, J.: Accelerated self-diffusion in fcc metals due to H induced superabundant vacancies. TMS 2012 Meeting, Orlando, FL, USA (2012)
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
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
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.