Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Ab Initio Guided Design of bcc Ternary Mg–Li–X (X=Ca,Al,Si,Zn,Cu) Alloys for Ultra-Lightweight Applications. Advanced Engineering Materials 12 (7), pp. 572 - 576 (2010)
von Pezold, J.; Dick, A.; Friák, M.; Neugebauer, J.: Generation and performance of special quasirandom structures for studying the elastic properties of random alloys: Application to Al–Ti. Physical Review B 81 (9), pp. 094203-1 - 094203-7 (2010)
Udyansky, A.; von Pezold, J.; Bugaev, N. V.; Friák, M.; Neugebauer, J.: Interplay between long-range elastic and short-range chemical interactions in Fe–C martensite formation. Physical Review B 79 (22), pp. 224112-1 - 224112-5 (2009)
Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Using ab initio calculations in designing bcc Mg-Li alloys for ultra light-weight applications. Acta Materialia 57 (1), pp. 69 - 76 (2009)
Lymperakis, L.; Friák, M.; Neugebauer, J.: Atomistic calculations on interfaces: Bridging the length and time scales. The European Physics Journal Special Topics 177, pp. 41 - 57 (2009)
Ma, D.; Friák, M.; Neugebauer, J.; Raabe, D.; Roters, F.: Multiscale simulation of polycrystal mechanics of textured β-Ti alloys using ab initio and crystal-based finite element methods. Physica Status Solidi B 245 (12), pp. 2642 - 2648 (2008)
Friák, M.; Counts, W. A.; Raabe, D.; Neugebauer, J.: Error-propagation in multiscale approaches to the elasticity of polycrystals. Physica Status Solidi (B) 245, pp. 2636 - 2641 (2008)
Counts, W. A.; Friak, M.; Battaile, C. C.; Raabe, D.; Neugebauer, J.: A comparison of polycrystalline elastic constants computed by analytic homogenization schemes and FEM. Physica Status Solidi B 245, pp. 2630 - 2635 (2008)
Sob, M.; Friák, M.; Wang, L. G.; Kuriplach, J.: The role of ab initio electronic structure calculations in contemporary materials science - part 2. Journal of Functional Materials 1 (11), pp. 408 - 418 (2007)
Sob, M.; Friák, M.; Wang, L. G.; Kuriplach, J.: The role of ab initio electronic structure calculations in contemporary materials science - part 1. Journal of Functional Materials 1 (10), pp. 363 - 367 (2007)
Raabe, D.; Sander, B.; Friák, M.; Ma, D.; Neugebauer, J.: Theory-guided bottom-up design of β-titanium alloys as biomaterials based on first principles calculations: Theory and experiments. Acta Materialia 55 (13), pp. 4475 - 4487 (2007)
Friák, M.; Raabe, D.; Neugebauer, J.: Ab Initio Guided Design of Materials. In: Structural Materials and Processes in Transportation, pp. 481 - 495 (Eds. Lehmhus, D.; Busse, M.; Herrmann, A. S.; Kayvantash, K.). Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany (2013)
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
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
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.
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.