Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Efficient approach to compute melting properties fully from ab initio with application to Cu. MPIE-ICAMS workshop, Ebernburg, Germany (2017)
Grabowski, B.: Data driven engineering of advanced materials: Combining high precision and scale bridging. Colloquium at Forschungszentrum Jülich, Jülich, Germany (2017)
Grabowski, B.: Development and application of quantum mechanics based simulation tools for the design of modern metallic materials. Seminar at RWTH Aachen, Aachen, Germany (2017)
Grabowski, B.: Discovery of an ordered hexagonal superstructure in an Al–Hf–Sc–Ti–Zr high entropy alloy. Seminar at University of Münster, Münster, Germany (2016)
Grabowski, B.: Discovery of an orderered hexagonal superstructure in an Al–Hf–Sc–Ti–Zr high entropy alloy. Seminar, Universität Münster, Münster, Germany (2016)
Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Development of methodologies to efficiently compute melting properties fully from ab initio. 2nd German-Dutch Workshop on Computational Materials Science, Domburg, The Netherlands (2016)
Grabowski, B.: Entwicklung von quantenmechanischen Simulationsmethoden für das Design moderner metallischer Werkstoffe. Seminar at University Paderborn, Paderborn, Germany (2016)
Grabowski, B.: Entwicklung von quantenmechanischen Simulationsmethoden für das Design moderner metallischer Werkstoffe. Seminar at Universität Paderborn, Paderborn, Germany (2016)
Körmann, F.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Lattice excitations in magnetic alloys: Recent advances in ab initio modeling of coupled spin and atomic fluctuations. TMS Annual Meeting 2016, Nashville, TN, USA (2016)
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
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…
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…