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)
Hickel, T.; Uijttewaal, M.; Neugebauer, J.: First principles determination of phase transitions in magnetic shape memory alloys. DPG Spring Meeting 2009, 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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…