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
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…
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…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…