Schwan, M.; Naikade, M. K.; Raabe, D.; Ratke, L.: From hard to rubber-like: mechanical properties of resorcinol-formaldehyde aerogels. Journal of Materials Science 50 (16), pp. 5482 - 5493 (2015)
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
It is very challenging to simulate within DFT extreme electric fields (a few 1010 V/m) at a surface, e.g. for studying field evaporation, the key mechanism in atom probe tomography (APT). We have developed a straight-forward scheme to incorporate an ideal plate counter-electrode in a nominally charged repeated-slab calculation by means of a generalized dipole correction of the standard electrostatic potential obtained from fully periodic FFT.
Magnetic materials enable the electrification of transport, communication, energy, and manufacturing. They serve for instance as hard magnets in electrical motors or as soft magnets in transformers. Their remanence, coercivity, and hysteresis losses determine the efficiency of devices that are urgently needed for enabling society and economy to use…
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…
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…
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.