Friák, M.; Sander, B.; Ma, D.; Raabe, D.; Neugebauer, J.: Theory-guided design of Ti-binaries for human implants. XVI. International Materials Research Congress, Cancun (Merrida), Mexico (2007)
Friák, M.; Sander, B.; Ma, D.; Raabe, D.; Neugebauer, J.: Ab initio prediction of elastic and thermodynamic properties of metals. Seminar in Friedrich-Alexander-Universitaet, Erlangen-Nürnberg, Germany (2007)
Friak, M.; Sander, B.; Ma, D.; Raabe, D.; Neugebauer, J.: Theory-guided design of Ti–Nb alloys for biomedical applications. 1st International Conference on Material Modelling, Dortmund, Germany (2009)
Friák, M.; Ma, D.; Sander, B.; Raabe, D.; Neugebauer, J.: Bottom up design of novel titanium-based biomaterials through the combination of ab-initio simulations and experimental methods. Euromat 2007, Nürnberg, Germany (2007)
Ma, D.; Raabe, D.; Roters, F.: Effects of initial orientation, sample geometry and friction on anisotropy and crystallographic orientation changes in single crystal microcompression deformation: A crystal plasticity finite element study. International workshop on small scale plasticity, Brauwald, Switzerland (2007)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…