Dutta, B.; Körmann, F.; Hickel, T.; Neugebauer, J.: Temperature-driven effects in functional materials: Ab initio insights. Talk at University Pierre and Marie CURIE (UPMC), Paris, France (2017)
Dutta, B.; Olsen, R. J.; Mu, S.; Hickel, T.; Samolyuk, G. D.; Specht, E. D.; Bei, H.; Lindsay, L. R.; Neugebauer, J.; Stocks , M.et al.; Larson, B. C.: Lattice dynamics in high entropy alloys: understanding the role of fluctuations. EUROMAT 2017, Thessaloniki, Greece (2017)
Dey, P.; Yao, M.; Friák, M.; Hickel, T.; Raabe, D.; Neugebauer, J.: Ab-initio investigation of the role of kappa carbide in upgrading Fe–Mn–Al–C alloy to the class of advanced high-strength steels. ArcelorMittal Global R&D Gent, Thessaloniki, Greece (2017)
Dutta, B.; Hickel, T.; Neugebauer, J.: Finite temperature excitation mechanisms and their coupling in magnetic shape memory alloys. The Materials Research Centre (MRC), Indian Institute of Science (IISc), Bangalore, India (2017)
Dutta, B.; Begum, V.; Hickel, T.; Neugebauer, J.: Impact of doping on the magnetic and structural transformations in magnetocaloric materials. DPG Spring Meeting of the Condensed Matter Section, Dresden, Germany (2017)
Dutta, B.; Hickel, T.; Neugebauer, J.: Ab initio modelling of phase diagrams in magnetic Heusler alloys: achievements and future challenges. SUSTech Global Scientists Forum, Shenzhen, China (2017)
Hickel, T.: New Insights into H trapping and Diffusion in Metallic Microstructures Obtained from Atomistic Simulations. 2016 International Hydrogen Conference, Jackson Lake Lodge, Moran, WY, USA (2016)
Dutta, B.; Hickel, T.; Neugebauer, J.: Intermartensitic Phase Boundaries in Ni–Mn–Ga Alloys: A Viewpoint from Ab initio Thermodynamics. 5th International Conference on Ferromagnetic Shape Memory Alloys, Sendai, Japan (2016)
Zendegani, A.; Körmann, F.; Hickel, T.; Hallstedt, B.; Neugebauer, J.: Thermodynamic properties of the quaternary Q phase in Al–Cu–Mg–Si: a combined ab-initio, phonon and compound energy formalism approach. International Conference on Advanced Materials Modelling (ICAMM), Rennes, France (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
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.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.