Raabe, D.; Li, Y.; Ponge, D.; Sandlöbes, S.; Choi, P.-P.; Hickel, T.; Kirchheim, R.; Neugebauer, J.: Nanoscale Transformations in Steels. German-Chinese High-level Workshop on “Microstructure-driven Design and Performance of Advanced Metals”, Institute of Metals Research (IMR) of the Chinese Academy of Science (CAS), Shenyang, China (2013)
Cheng, S.-T.; Todorova, M.; Neugebauer, J.: Interactions of oxidizing species with the Mg(0001) surface: The role of electrostatic contributions. DPG Frühjahrstagung, Regensburg, Germany (2013)
Neugebauer, J.: Fully ab initio determination of free energies: Basis for high-throughput approaches in materials design. DPG Frühjahrstagung 2013, Regensburg, Germany (2013)
Todorova, M.; Neugebauer, J.: Extending the Concept of Semiconductor Defect Chemistry to Electrochemistry. TMS Annual Meeting, San Antonio, TX, USA (2013)
Bleskov, I.; Hickel, T.; Neugebauer, J.: Impact of Local Magnetism on Planar Defects in Pure Iron. SFB-761 Annual Meeting 2013, Herdecke, Germany (2013)
Bleskov, I.; Körmann, F.; Hickel, T.; Neugebauer, J.: Impact of Magnetism on Thermodynamic Properties of Iron. International Symposium “Frontiers In Electronic Structure Theory And Multi Scale Modeling” (FEST-VEK), Moscow, Russia (2013)
Freysoldt, C.; Pfanner, G.; Neugebauer, J.: Defects in amorphous silicon from H insertion. Workshop "Spins as Functional Probes in Solar Energy Research", Berlin, 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.
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…