Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Pressure dependence of the Curie temperature in bcc iron studied by ab initio simulations. Physical Review B 79, 184406, pp. 184406-1 - 184406-5 (2009)
Körmann, F.; Kienert, J.; Schwieger, S.; Nolting, W.: Cu cap layer on Ni8/Cu(001): reorientation and Tc-shift. The European Physical Journal B 65, pp. 499 - 504 (2008)
Körmann, F.; Dick, A.; Grabowski, B.; Hallstedt, B.; Hickel, T.; Neugebauer, J.: Free energy of bcc iron: Integrated ab initio derivation of vibrational, electronic, and magnetic contributions. Physical Review B 78, 033102 (2008)
Neugebauer, J.; Glensk, A.; Leyson, G. P. M.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio description of finite temperature phase stabilities and transformations. In: PTM 2015 - Proceedings of the International Conference on Solid-Solid Phase Transformations in Inorganic Materials 2015, pp. 751 - 752 (Eds. Chen, L.-Q.; Militzer, M.; Botton, G.; Howe, J.; Sinclair, C. W. et al.). International Conference on Solid-Solid Phase Transformations in Inorganic Materials 2015, PTM 2015, Whistler, BC, Canada, June 28, 2015 - July 03, 2015. PTM 2015, Whistler, British Columbia (2015)
Neugebauer, J.; Körmann, F.; Ferrari, A.: Navigating and exploiting the high-dimensional configuration spaces of high entropy alloys. The 11th International Conference on Multiscale Materials Modeling, Prague, Czech Republic (2023)
Gong, Y.; Ikeda, Y.; Körmann, F.; Neugebauer, J.: Ab initio computation of phase stability and interstitial alloying in bcc compositionally complex alloys. International Conference on High-Entropy Materials (ICHEM 2023), Knoxville, TN, USA (2023)
Neugebauer, J.; Körmann, F.; Hickel, T.: Ab Initio Descriptors to Guide Materials Design in High-dimensional Chemical and Structural Configuration Spaces. TMS Annual Meeting and Exhibition, San Diego, CA, USA (2022)
Neugebauer, J.; Ikeda, Y.; Körmann, F.: Materials design based on efficient sampling of high dimensional chemical and thermodynamic configuration spaces. Workflows for Atomistic Simulations, Ruhr-Universität Bochum, Online Meeting, Bochum, Germany (2021)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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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It is very challenging to simulate electron-transfer reactions under potential control within high-level electronic structure theory, e. g. to study electrochemical and electrocatalytic reaction mechanisms. We develop a novel method to sample the canonical NVTΦ or NpTΦ ensemble at constant electrode potential in ab initio molecular dynamics…
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…
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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…