Neugebauer, J.: The role of hydrogen-hydrogen interaction in understanding H embrittlement: An ab initio guided multiscale approach. Hydrogen Conference, London, UK (2014)
Neugebauer, J.: Ab initio based design of structural materials: Status and challenges. Expertenpanel Computer Simulation of Material Structures and Properties, Schott AG , Mainz, Germany (2014)
Zhang, X.; Hickel, T.; Rogal, J.; Drautz, R.; Neugebauer, J.: Atomistic origin of structural modulations in Fe ultrathin film and impact for structural transformations in Fe–C alloys. ADIS Workshop 2014, Ringberg, Germany (2014)
Neugebauer, J.: Computational coarse-graining in configuration space as basis for a predictive ab initio thermodynamics. EPSRC Symposium, Warwick, London, UK (2013)
Körmann, F.; Grabowski, B.; Palumbo, M.; Fries, S. G.; Hickel, T.; Neugebauer, J.: Strong and weak magnetic coupling in chromium. ICAMS Advanced Discussions - Current Developments, Ruhr-Universität-Bochum, Bochum, Germany (2013)
Grabowski, B.; Glensk, A.; Korbmacher, D.; Huang, L.; Körmann, F.; Hickel, T.; Neugebauer, J.: First principles at finite temperatures: New approaches and massively parallel computations. CMSI International Symposium 2013: Extending the power of computational materials sciences with K-computer, Ito International Research Center, University of Tokyo, Japan (2013)
Hickel, T.; Nazarov, R.; Neugebauer, J.: Aspekte der Wasserstoffversprödung von Stählen: Verständnisgewinn durch quantenmechanische Simulationen. AKE Workshop, DECHEMA, Frankfurt a. M, Germany (2013)
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…