Grabowski, B.: Modern materials design from first-principles: Recent progress and future prospects. Seminar, Imperial College London, London, UK (2015)
Grabowski, B.: Ab initio thermodynamics of the CoCrFeMnNi high entropy alloy: Importance of entropy contributions beyond the configurational one. ICAMS Seminar, Ruhr-University Bochum, Bochum, Germany (2015)
Grabowski, B.: Random phase approximation up to the melting point: The impact of anharmonicity and non-local many-body effects on the thermodynamics of Au. MISIS Workshop, 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)
Grabowski, B.; Wippermann, S. M.; Glensk, A.; Hickel, T.; Neugebauer, J.: Random phase approximation up to the melting point: Impact of anharmonicity and nonlocal many-body effects on the thermodynamics of Au. DPG Spring Meeting 2015, Berlin, Germany (2015)
Hickel, T.; Glensk, A.; Grabowski, B.; Körmann, F.; Neugebauer, J.: Thermodynamics of materials up to the melting point: The role of anharmonicities. Asia Sweden Meeting on Understanding Functional Materials from Lattice dynamics, Guwahati, India (2014)
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.