Neugebauer, J.; Grabowski, B.; Körmann, F.; Dick, A.; Hickel, T.: Ab Initio Thermodynamics: Status, applications and challenges. The second Sino-German Symposium on “Computational Thermodynamics and Kinetics and Their Applications to Solidification”, Kornelimünster/Aachen, Germany (2009)
Freysoldt, C.; Neugebauer, J.; Van de Walle, C. G.: Fully ab initio supercell corrections for charged defects. CECAM workshop "Which Electronic Structure Method for the Study of Defects?", Lausanne, Switzerland (2009)
Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: First principles determination of phase transitions in magnetic shape memory alloys. 2nd Sino-German Symposium on Computational Thermodynamics and Kinetics and their Application to Solidification, Aachen, Germany (2009)
Neugebauer, J.: Computing free energy contributions of point defects. ECAM conference: Which Electronic Structure Method for the Study of Defects?, Lausanne, Switzerland (2009)
Neugebauer, J.: Materials Design Based On Ab Initio Thermodynamics And Kinetics: Present Status And Perspectives. Colloquium at Universität Gießen, Gießen, Germany (2009)
Hickel, T.; Grabowski, B.; Ismer, L.; Neugebauer, J.: Role of Atomistic Simulations in the Prediction of Thermodynamic Properties of Materials. Workshop on Multi-Scale Computational Materials Design of Structural Materials, POSCO international center, Pohang, South Korea (2009)
von Pezold, J.; Lymperakis, L.; Neugebauer, J.: A multiscale study of the Hydrogen enhanced local plasticity (HELP) mechanism. Asia Steel Conference 2009, Busan, South Korea (2009)
Dick, A.; Hickel, T.; Neugebauer, J.: First Principles Predictions of Stacking Fault Properties in FeMn Alloys. Asia Steel Conference 2009, Busan, South Korea (2009)
Neugebauer, J.: Multi-Scale Computational Materials Design of Structural Materials: First-Principles Calculations. Workshop at Pohang University of Science and Technology, Pohang, South Korea (2009)
Neugebauer, J.: Ab initio based multiscale modeling of engineering materials: From a predictive thermodynamic description to tailored mechanical properties. Asia Steel Conference, Busan, South Korea (2009)
Neugebauer, J.: Ab Initio Based Multiscale Modeling of Engineering Materials: From a Predictive Thermodynamic Description to Tailored Mechanical Properties. Colloquium at TU Bergakademie Freiberg, Freiberg, Germany (2009)
Nazarov, R.; Ismer, L.; Hickel, T.; Neugebauer, J.: Wasserstoff in X-IP Stahl (ab initio) Einfluss von Defekten auf die Energetik und Dynamik von Wasserstoff in Manganstählen. X-IP Workshop, Dortmund, Germany (2009)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: What can EPR hyperfine parameters tell about the Si dangling bond? - A theoretical viewpoint. 1st International Workshop on the Staebler-Wronski effect, Berlin, Germany (2009)
Udyansky, A.; von Pezold, J.; Friák, M.; Neugebauer, J.: Multi-scale modeling of the phase stability of interstitial Fe-C solid solutions. Invited talk at MPI for Metal Research, Stuttgart, Germany (2009)
Aydin, U.; Ismer, L.; Hickel, T.; Neugebauer, J.: Universal trends for the solubility of hydrogen in non-magnetic 3d transition metals derived from first principles. DPG Spring meeting, Dresden, Germany (2009)
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.
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…