von Pezold, J.; Lymperakis, L.; Neugebauer, J.: Hydrogen-enhanced plasticity at dilute bulk H concentrations: The role of H-H interactions and the formation of local hydrides. Acta Materialia 59, pp. 2969 - 2980 (2011)
Abbasi, A.; Dick, A.; Hickel, T.; Neugebauer, J.: First-principles investigation of the effect of carbon on the stacking fault energy of Fe–C alloys. Acta Materialia 59, pp. 3041 - 3048 (2011)
Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Using ab initio calculations in designing bcc MgLi–X alloys for ultra-lightweight applications. Advanced Engineering Materials 12 (12), pp. 1198 - 1205 (2010)
Nazarov, R.; Hickel, T.; Neugebauer, J.: First-principles study of the thermodynamics of hydrogen-vacancy interaction in fcc iron. Physical Review B 82 (22), pp. 224104-1 - 224104-11 (2010)
Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Ab Initio Guided Design of bcc Ternary Mg–Li–X (X=Ca,Al,Si,Zn,Cu) Alloys for Ultra-Lightweight Applications. Advanced Engineering Materials 12 (7), pp. 572 - 576 (2010)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Native and hydrogen-containing point defects in Mg3N2: A density functional theory study. Physical Review B 81, 224109, pp. 1 - 10 (2010)
Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Rescaled Monte Carlo approach for magnetic systems: Ab initio thermodynamics of bcc iron. Physical Review B 81 (13), pp. 134425 - 134434 (2010)
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
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.