Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Development of methodologies to efficiently compute melting properties fully from ab initio. 2nd German-Dutch Workshop on Computational Materials Science, Domburg, The Netherlands (2016)
Neugebauer, J.: Hydrogen embrittlement research at the MPIE (Max-Planck-Institut für Eisenforschung). SNEAC Workshop Environmental Assisted Cracking, Trondheim, Norway (2016)
Dutta, B.; Hickel, T.; Neugebauer, J.: Phase diagrams in magnetic shape memory alloys: Insights obtained from ab initio thermodynamics. The forty-fifth International Conference on Computer Coupling of Phase Diagrams and Thermochemistry, Awaji Island, Hyogo, Japan (2016)
Neugebauer, J.: Ab initio determination of lattice stabilities and comparison to CALPHAD. Plenary talk, CALPHAD XLV Conference, Awaji Island, Japan (2016)
Surendralal, S.; Todorova, M.; Neugebauer, J.: Automated calculations for charged point defects in MgO and α-Fe2O3. DPG-Frühjahrstagung 2016, Regensburg, Germany (2016)
Dutta, B.; Debashish, D.; Ghosh, S.; Sanyal, B.; Hickel, T.; Neugebauer, J.: Intricacies of phonon line shapes in random alloys: A first-principles study. DPG Spring Meeting of the Condensed Matter Section, Regensburg, Germany (2016)
Dutta, B.; Begum, V.; Hickel, T.; Neugebauer, J.: Impact of point defects on the phase stability in Heusler alloys: A first-principles study. DPG Spring Meeting of the Condensed Matter Section, Regensburg, Germany (2016)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Ab initio Determination of Formation Energies and Charge Transfer Levels of Charged Ions in Water. APS 2016, Baltimore, MD, USA (2016)
Vatti, A. K.; Todorova, M.; Neugebauer, J.: Formation Energy of Ions in Water using ab-initio Molecular Dynamics. DPG Frühjahrstagung 2016, Regensburg, Germany (2016)
Neugebauer, J.: The digital transformation in Materials Science from a Modellers Perspective. VDI Workshop „Digitale Transformation in der Werkstofftechnik”, Düsseldorf, Germany (2016)
Körmann, F.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Lattice excitations in magnetic alloys: Recent advances in ab initio modeling of coupled spin and atomic fluctuations. TMS Annual Meeting 2016, Nashville, TN, USA (2016)
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
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.