Hickel, T.; Uijttewaal, M.; Grabowski, B.; Neugebauer, J.: Determination of symmetry reduced structures by a soft-phonon analysis in magnetic shape memory alloys. Theory meets industry. The impact of density-functional calculation on materials science, Vienna, Austria (2007)
Grabowski, B.; Hickel, T.; Neugebauer, J.: Accuracy and error bars of DFT calculated thermodynamic properties for elementary metals. 13th International Workshop on Computational Physics and Materials Science: Total Energy and Force Methods, Trieste, Italy (2007)
Hickel, T.; Grabowski, B.; Uijttewaal, M.; Neugebauer, J.: Determination of symmetry-reduced structures by a soft-phonon analysis in magnetic shape memory alloys. 13th International Workshop on Computational Physics and Materials Science: Total Energy and Force Methods, Trieste, Italy (2007)
Hickel, T.; Grabowski, B.; Neugebauer, J.; Neumann, B.; Neumann, K.-U.; Ziebeck, K. R. A.: Temperature dependent properties of the Heusler alloy Ni2+xMn1-xGa. International Workshop on Ab initio Description of Iron and Steel (ADIS2006), Status and future challenges, Ringberg Castle, Germany (2006)
Hickel, T.; Nolting, W.: A self-consistent projection-operator approach to the Kondo-lattice model. The International Conference on Strongly Correlated Electron Systems, Vienna, Austria (2005)
Hickel, T.; Grabowski, B.; Neumann, K.; Neumann, K.-U.; Ziebeck, K. R. A.; Neugebauer, J.: Temperature dependent properties of Ni-rich Ni2MnGa. Materials Research Society fall meeting, Boston, MA, USA (2005)
Hickel, T.: Introduction to Quantum Mechanics in Solid-State Physics. Lecture: Masterstudiengang „Materials Science and Simulation“, WS 2015/2016, Ruhr-Universität Bochum, Bochum, Germany, October 01, 2015 - March 31, 2016
Hickel, T.: Introduction to Quantum Mechanics in Solid-State Physics. Lecture: Masterstudiengang „Materials Science and Simulation“, WS 2014/2015, Ruhr-Universität Bochum, Bochum, Germany, October 01, 2014 - March 31, 2015
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 (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…