Todorova, M.; Yoo, S.-H.; Surendralal, S.; Neugebauer, J.: Predicting atomic structure and chemical reactions at solid-liquid interfaces by first principles. Operando surface science – Atomistic insights into electrified solid/liquid interfaces (708. WE-Heraeus-Seminar), Physikzentrum, Bad Honnef, Germany (2019)
Neugebauer, J.: Machine Learning in Materials: Screening and Discovery. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan (2019)
Ikeda, Y.; Ishibashi, S.; Neugebauer, J.; Körmann, F.: Tuning stacking-fault energies and local lattice distortions in high-entropy alloys. Theory of Complex Disorder in Materials (TCDM2019) , Linköping, Sweden (2019)
Neugebauer, J.; Surendralal, S.; Todorova, M.: First-principles appraoch to model electrochemical reactions at solid-liquid interfaces. ACS 2019 Fall Meeting & Exhibition, San Diego, CA, USA (2019)
Todorova, M.; Surendralal, S.; Neugebauer, J.: Degradation processes at surfaces and interfaces. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany (2019)
Neugebauer, J.; Huber, L.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio input for multiphysics models: Accuracy, performance and challenges. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Erlangen, Germany (2019)
Neugebauer, J.: Machine Learning in Materials: Screening and Discovery. Gordon Research Conference Physical Metallurgy „Coupling Computation, Data Science and Experiments in Physical Metallurgy“, Manchester, NH, USA (2019)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
A high degree of configurational entropy is a key underlying assumption of many high entropy alloys (HEAs). However, for the vast majority of HEAs very little is known about the degree of short-range chemical order as well as potential decomposition. Recent studies for some prototypical face-centered cubic (fcc) HEAs such as CrCoNi showed that…
Electron channelling contrast imaging (ECCI) is a powerful technique for observation of extended crystal lattice defects (e.g. dislocations, stacking faults) with almost transmission electron microscopy (TEM) like appearance but on bulk samples in the scanning electron microscope (SEM).
About 90% of all mechanical service failures are caused by fatigue. Avoiding fatigue failure requires addressing the wide knowledge gap regarding the micromechanical processes governing damage under cyclic loading, which may be fundamentally different from that under static loading. This is particularly true for deformation-induced martensitic…
We simulate the ionization contrast in field ion microscopy arising from the electronic structure of the imaged surface. For this DFT calculations of the electrified surface are combined with the Tersoff-Hamann approximation to electron tunneling. The approach allows to explain the chemical contrast observed for NiRe alloys.
Decarbonisation of the steel production to a hydrogen-based metallurgy is one of the key steps towards a sustainable economy. While still at the beginning of this transformation process, with multiple possible processing routes on different technological readiness, we conduct research into the related fundamental scientific questions at the MPIE.
Within this project, we will use an infra-red laser beam source based selective powder melting to fabricate copper alloy (CuCrZr) architectures. The focus will be on identifying the process parameter-microstructure-mechanical property relationships in 3-dimensional CuCrZr alloy lattice architectures, under both quasi-static and dynamic loading…