Freysoldt, C.; Pfanner, G.; Neugebauer, J.: The Dangling-Bond Defect in Amorphous Silicon: Statistical Random Versus Kinetically Driven Defect Geometries. 24th International Conference on Amorphous and Nanocrystalline Semiconductors (ICANS 24), Nara, Japan (2011)
Gutierrez-Urrutia, I.; Dick, A.; Hickel, T.; Neugebauer, J.; Raabe, D.: Understanding TWIP steel microstructures by using advanced electron microscopy and ab initio predictions. International Conference on Processing & Manufacturing of Advanced Materials THERMEC 2011, Québec City, QC, Canada (2011)
Hickel, T.; Al-Zubi, A.; Neugebauer, J.: Chemical Trends for Phase Transitions in Magnetic Shape Memory Alloys Derived from First Principles. International Conference on Ferromagnetic Shape-Memory Alloys, ICFSMA’11, Dresden, Germany (2011)
Nazarov, R.; Hickel, T.; Neugebauer, J.: H solubility in different steel phases: Influence of alloying elements and strain. HYDRAMICROS Workshop, Otaniemi, Finland (2011)
Duff, A.; Lymperakis, L.; Neugebauer, J.: Ab-initio based comparitive study of In incorporation and surface segregation on III- and N-face {0001} InGaN surfaces. 9th International Conference of Nitride Semi-Conductors, Glasgow, UK (2011)
Nazarov, R.; Hickel, T.; Neugebauer, J.: Thermodynamics and kinetics of hydrogen interaction with point defects. CM-Workshop, Attendorn, Germany (2011)
Fabritius, H.; Nikolov, S.; Hild, S.; Ziegler, A.; Friák, M.; Neugebauer, J.; Raabe, D.: Design principles of crustacean cuticle: From molecules to skeletal elements. Workshop „From Nanoparticle Assembly to Functional Polymer Components” at Department of Geo- and Environmental Sciences, LMU, München, Germany (2011)
Neugebauer, J.: Ab initio guided design of materials with superior mechanical properties. Colloquium, Institut für Technologie, Karlsruhe, Germany (2011)
Elstnerová, P.; Friák, M.; Neugebauer, J.: Enhancing mechanical properties of calcite by Mg substitutions - A Quantum-Mechanical Study. Multi-Scale Mechanics of Biological and Bio-Inspired Hierarchical Materials and Surfaces, Glasgow, UK (2011)
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
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.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
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…