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)
Neugebauer, J.: Ab Initio Thermodynamics: A Novel Route to Design Structural Materials with Superior Mechanical Properties. TMS-MEMA Conference, Doha, Katar (2015)
Neugebauer, J.: Design and discovery of structural materials on the computer: Prospects and challenges. Colloquium at Universität Magdeburg, Magdeburg, Germany (2015)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Formation Energy of ions in water: An ab initio molecular dynamics study. 2nd German-Austrian Workshop on "Computational Materials Science on Complex Energy Landscapes", Kirchdorf, Austria (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)
Neugebauer, J.: Efficient coarse graining of stochastic high-dimensional configuration spaces as fundament for a fully ab initio based materials design. Colloquium WIAS, Berlin, 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)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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…