Nikolov, S.; Raabe, D.: Hierarchical Modeling of the Elastistic Properties of Bone at Submicron Scales: The Role of Extrafibrillar Mineralization. Biophysical Journal 94, pp. 4220 - 4232 (2008)
Nikolov, S.; Lebensohn, R. A.; Raabe, D.: Self-consistent modeling of large plastic deformation, texture and morphology evolution in semi-crystalline polymers. Journal of the Mechanics and Physics of Solids 54 (7), pp. 1350 - 1375 (2006)
Nikolov, S.; Han, C. S.; Raabe, D.: On the origin of size effects in small-strain elasticity of solid polymers. International Journal of Solids and Structures 44, pp. 1582 - 1592 (2006)
Han, C. S.; Nikolov, S.: Frank energy and size dependent deformation in polymer. 13th International Symposium on Plasticity and its Current Applications, Alaska [USA], June 02, 2007 - June 06, 2007., (2008)
Nikolov, S.; Sachs, C.; Fabritius, H.; Raabe, D.; Petrov, M.; Friak, M.; Neugebauer, J.; Lymperakis, L.; Ma, D.: Hierarchical modeling of the mechanical properties of lobster cuticle from nano‐ up to macroscale: The influence of the mineral content and the microstructure. In: Proceedings of MMM 2008 "Computational Modeling of biological and soft condensed matter systems", pp. 667 - 670. 4th International Conference on Multiscale Materials Modeling, Tallahassee, FL, USA, October 27, 2008 - October 31, 2008. Dep. of Scientific Computing, Florida State University, USA (2008)
Nikolov, S.; Roters, F.; Raabe, D.: A constitutive model with shear transformation zones plasticity and reptation-based viscoelasticity. 3th Int. Conference Multiscale Materials Modeling 2006, Freiburg, Germany, September 18, 2006 - September 22, 2006. (2006)
Nikolov, S.; Lebensohn, R. A.; Roters, F.; Raabe, D.; Ma, A.: Micromechanical modeling of large plastic deformation in semi-crystalline polymers. 12th International Symposium on Plasticity 2006, Halifax, Nova Scotia (Canada), July 17, 2006 - July 22, 2006. (2006)
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
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.