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)
Neugebauer, J.: Free energy sampling strategies for structurally complex materials. Workshop II: Stochastic Sampling and Accelerated Time Dynamics on Multidimensional Surfaces, IPAM, UCLA, Los Angeles, CA, USA (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)
Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Efficient approach to compute melting properties fully from ab initio with application to Cu. MPIE-ICAMS workshop, Ebernburg, Germany (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)
Neugebauer, J.: Fundamental compositional limitations in the thin film growth of metastable alloys. Rapidly Quenched & Metastable Materials 16, Leoben, Austria (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)
Neugebauer, J.: From Semiconductors to High-Strength Steels and Back Again. 10 years of the Laboratory for Photovoltaics & Semiconductor Physics, Luxembourg, Luxembourg (2017)
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
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.
While Density Functional Theory (DFT) is in principle exact, the exchange functional remains unknown, which limits the accuracy of DFT simulation. Still, in addition to the accuracy of the exchange functional, the quality of material properties calculated with DFT is also restricted by the choice of finite bases sets.
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…
The structures of grain boundaries (GBs) have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the near-atomic scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability…
Hydrogen embrittlement is one of the most substantial issues as we strive for a greener future by transitioning to a hydrogen-based economy. The mechanisms behind material degradation caused by hydrogen embrittlement are poorly understood owing to the elusive nature of hydrogen. Therefore, in the project "In situ Hydrogen Platform for…