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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.