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)
Todorova, M.; Surendralal, S.; Neugebauer, J.: Building an ab-initio potentiostat in a standard DFT code with periodic boundary conditions. ELRC2019 - IPAM reuniuon workshop, Lake Arrowhead, CA, USA (2019)
Zhu, L.-F.; Janßen, J.; Grabowski, B.; Neugebauer, J.: Melting parameters from ab initio using the fast statistical sampling TOR-TILD approach: Applications to Al and Ni. CALPHAD XLVIII CONFERENCE, Singapore, Singapore (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 novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.