Dey, P.; Nazarov, R.; Yao, M.; Friák, M.; Hickel, T.; Neugebauer, J.: Adaptive C content in coherently strained kappa-carbides - An ab initio explanation of atom probe tomography data. 2nd German-Austrian Workshop on "Computational Materials Science on Complex Energy Landscapes", Kirchdorf, Austria (2015)
Dutta, B.; Körmann, F.; Hickel, T.; Neugebauer, J.: The itinerant coherent potential approximation for phonons: Role of fluctuations for systems with magnetic disorder. 2nd German-Austrian Workshop, Kirchdorf, Austria (2015)
Gupta, A.; Dutta, B.; Hickel, T.; Neugebauer, J.: Thermodynamic phase stability in the Al–Sc system using first principles methods. 2nd German-Austrian Workshop on "Computational Materials Science on Complex Energy Landscapes", Kirchdorf, Austria (2015)
Hickel, T.; Nazarov, R.; McEniry, E.; Dey, P.; Neugebauer, J.: Ab initio insights into the interaction of hydrogen with precipitates in steels. Workshop on Hydrogen Embrittlement and Sour Gas Corrosion 2015, Düsseldorf, Germany (2015)
Zendegani, A.; Körmann, F.; Hickel, T.; Neugebauer, J.: First-principles study of thermodynamic properties of the Q-phase in Al–Cu–Mg–Si. 2nd German-Austrian Workshop, Kirchdorf, Austria (2015)
Zhang, X.; Hickel, T.; Rogal, J.; Drautz, R.; Neugebauer, J.: Atomistic origin of structural modulations in Fe ultrathin films on Cu(001). 2nd German-Austrian Workshop, Kirchdorf, Austria (2015)
Hickel, T.: Understanding complex materials at finite temperatures by ab inito methods. Colloquium at Institut für Materialwissenschaft, Universtität Stuttgart, Stuttgart, Germany (2014)
Hickel, T.: Ab initio basierte Methoden der mechanismen-orientierten Werkstoffentwicklung. Colloquium at Salzgitter-Mannesmann-Forschung GmbH, Duisburg, Germany (2014)
Hickel, T.; Nazarov, R.; McEniry, E.; Dey, P.; Neugebauer, J.: Impact of light elements on interface properties in steels. CECAM workshop “Modeling Metal Failure Across Multiple Scales”, Lausanne, Switzerland (2014)
Hickel, T.: Understanding complex materials at finite temperatures by ab inito methods. Physikalisches Kolloquium der TU Chemnitz, Chemnitz, Germany (2014)
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…