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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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
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.
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…