Counts, W. A.; Friák, M.; Battaile, C.; Raabe, D.; Neugebauer, J.: Multiscale Prediction of Polycrystal Elastic Properties of Ultralight Weight Mg-Li Alloys using Ab Initio and FEM Approaches. MRS Fall Conference 2008, Boston, MA, USA (2008)
Counts, W. A.; Ma, D.; Friák, M.; Neugebauer, J.; Raabe, D.: Multiscale design of aluminium alloys based on ab-initio methods. ICAA 11 – 11th International Conference on Aluminium Alloys 2008, Aachen, Germany (2008)
Raabe, D.; Friak, M.; Neugebauer, J.; Counts, W. A.: Homogenization in Polycrystal Mechanics on the Basis of First Principles Simulations. IUTAM Symposium on Variational Concepts in Materials Mechanics, Ruhr-Universität Bochum, Germany (2008)
Friák, M.; Sander, B.; Ma, D.; Counts, W. A.; Raabe, D.; Neugebauer, J.: Ab-initio based multi-scale approaches to the elasticity of polycrystals. Mid-term COST conference on Multiscale Modeling of Materials, COST action 19, Brno, Czech Republic (2008)
Counts, W. A.: FEM: A Basic Overview of the Method & Outlook on Applications. MPIE inter-departmental tutorial day(s) 2008, MPI für Eisenforschung GmbH, Düsseldorf, Germany (2008)
Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Using Ab Initio to Predict Engineering Parameters in bcc Magnesium-Lithium Alloys. American Physics Society March Meeting, New Orleans, LA, USA (2008)
Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Using Ab Initio to Predict Engineering Parameters in bcc Magnesium-Lithium Alloys. Deutsche Physikalische Gesellschaft Meeting, Berlin, Germany (2008)
Nikolov, S.; Sachs, C.; Counts, W. A.; Fabritius, H.; Raabe, D.: Modeling of the Mechanical Behavior of Bone at Submicron Scale through Mean-Field Homogenization. European Congress and Exhibition on Advanced Materials and Processes (EUROMAT 2007), Nürnberg, Germany (2007)
Friák, M.; Counts, W. A.; Raabe, D.; Neugebauer, J.: Identification of fundamental materials-design limits in ultra light-weight Mg–Li alloys via quantum-mechanical calculations. Materials Science and Engineering 2010, Darmstadt, Germany (2010)
Counts, W. A.: FEM: A Basic Overview of the Method & Outlook on Applications. Lecture: Aachen Institute for Advanced Studies in Computational Engineering and Science (AICES), Aachen, Germany, 2008-09
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
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…
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 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.