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
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