Dick, A.; Hickel, T.; Neugebauer, J.: First Principles Predictions of Stacking Fault Properties in FeMn Alloys. Asia Steel Conference 2009, Busan, South Korea (2009)
Körmann, F.; Dick, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: The free energy of iron: Integrated ab initio derivation of vibrational, electronic, and magnetic contributions. DPG Spring Meeting 2009, Dresden, Germany (2009)
Dick, A.; Hickel, T.; Neugebauer, J.: First Principles Predictions of Mechanical Properties of FeMn-Alloys. Workshop des SFB761, Beilngries, Germany (2008)
Körmann, F.; Dick, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: The free energy of bcc iron: Integrated ab initio derivation of vibrational, electronic, and magnetic contributions. Computational Materials Science Workshop, Ebernburg Castle, Germany (2008)
Körmann, F.; Dick, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: The free energy of bcc iron: Integrated ab initio derivation of vibrational, electronic, and magnetic contributions. International Workshop on Ab initio Description of Iron and Steel (ADIS2008), Ringberg Castle, Germany (2008)
Dick, A.; Neugebauer, J.: Ab initio STM and STS simulations on magnetic and nonmagnetic metallic surfaces. Computational Materials Science Workshop, Goslar, Germany (2007)
Abu-Farsakh, H.; Dick, A.; Neugebauer, J.: Incorporation of N at GaAs and InAs surfaces. Deutsche Physikalische Gesellschaft Spring Meeting of the Division Condensed Matter, Dresden, Germany (2006)
Dick, A.; Neugebauer, J.: Probing of bulk band edges by STM: An ab initio analysis. Deutsche Physikalische Gesellschaft - Spring Meeting of the Division Condensed Matter, Dresden, Germany (2006)
Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Integrating finite temperature magnetism into ab initio free energy calculations. Calphad XL, Rio de Janeiro, Brazil (2011)
Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Integrating finite temperature magnetism into ab initio free energy calculations. TMS 2011 Annual Meeting, San Diego, CA, USA (2011)
Udyansky, A.; von Pezold, J.; Dick, A.; Neugebauer, J.: Martensite formation in dilute Fe-based solid solutions: Ab initio based multi-scale approach. Ab initio Description of Iron and Steel: Mechanical properties, 468. Wilhelm und Else Heraeus-Seminar, Ringberg, Germany (2010)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.