Friák, M.; Sob, M.; Kim, O.; Ismer, L.; Neugebauer, J.: Ab initio calculation of phase boundaries in iron along the bcc-fcc transformation path and magnetism of iron overlayers. Seminar at the Department of Materials Physics at Montan Universität Leoben, Leoben, Austria (2009)
Neugebauer, J.: Materials Design based on Ab Initio Thermodynamics: Status, Perspectives, and Trends. Colloquium Talk at Institut für Materialprüfung, Werkstoffkunde und Festigkeitslehre, Universität Stuttgart, Stuttgart, Germany (2009)
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)
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
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.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…
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…