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
Crystal plasticity modelling has gained considerable momentum in the past 20 years [1]. Developing this field from its original mean-field homogenization approach using viscoplastic constitutive hardening rules into an advanced multi-physics continuum field solution strategy requires a long-term initiative. The group “Theory and Simulation” of…
The project focuses on development and design of workflows, which enable advanced processing and analyses of various data obtained from different field ion emission microscope techniques such as field ion microscope (FIM), atom probe tomography (APT), electronic FIM (e-FIM) and time of flight enabled FIM (tof-FIM).
The goal of this project is to develop an environmental chamber for mechanical testing setups, which will enable mechanical metrology of different microarchitectures such as micropillars and microlattices, as a function of temperature, humidity and gaseous environment.
The development of pyiron started in 2011 in the CM department to foster the implementation, rapid prototyping and application of the highly advanced fully ab initio simulation techniques developed by the department. The pyiron platform bundles the different steps occurring in a typical simulation life cycle in a single software platform and…
This work led so far to several high impact publications: for the first time nanobeam diffraction (NBD) orientation mapping was used on atom probe tips, thereby enabling the high throughput characterization of grain boundary segregation as well as the crystallographic identification of phases.
This project will aim at addressing the specific knowledge gap of experimental data on the mechanical behavior of microscale samples at ultra-short-time scales by the development of testing platforms capable of conducting quantitative micromechanical testing under extreme strain rates upto 10000/s and beyond.
The prediction of materials properties with ab initio based methods is a highly successful strategy in materials science. While the working horse density functional theory (DFT) was originally designed to describe the performance of materials in the ground state, the extension of these methods to finite temperatures has seen remarkable…
The balance between different contributions to the high-temperature heat capacity of materials can hardly be assessed experimentally. In this study, we develop computationally highly efficient ab initio methods which allow us to gain insight into the relevant physical mechanisms. Some of the results have lead to breakdown of the common…
