Data-driven methods for atomistic simulations
The research group is working on the application of data-driven methods in materials science with a particular focus on the atomic scale. A major research area is the automated extraction, analysis and validation of models in materials science, with specific application to interatomic potentials. We perform high-throughput calculations of materials properties at different levels of theory, including both density functional theory and effective interatomic potentials using the pyiron computational framework, which we co-develop with the Computational Materials Design department at the Max Planck Institute for iron research
Computational and data infrastructure for interatomic potentials validation. (Click image to enlarge.)
Another research area is the application of machine learning methods to large data sets, for example, from combinatorial or high-throughput methods and to provide efficient and supporting tools for materials discovery.
Pair plots of formation energies and band gaps of Al-Ga-In sesquioxides as calculated by density functional theory and predicted by surrogate machine learning models. (Click image to enlarge.)
Competences
- data-driven methods (machine learning) in materials science
- high-throughput calculations (DFT and molecular dynamics)
- interatomic potentials and their validation
- data management & visualization
Dr. Yury Lysogorskiy
ICAMS
Ruhr-Universität Bochum
44780 Bochum
Germany
Tel: +49 234 32 29300
Fax: +49 234 32 14977
Group Members
Recent publications
M. Rinaldi. Modelling magnetism from the electronic structure to continuum for iron and its alloys PhD Thesis, Ruhr-Univerisität Bochum (2022)
B. Xiao, Y. Lysogorskiy, A. Savan, H. Bögershausen et al. Correlations of composition, structure, and hardness in the high-entropy alloy system Nb–Mo–Ta–W High Entropy Alloys and Materials, Springer Science and Business Media LLC,, 1, 1-22, (2022)
A. Bochkarev, Y. Lysogorskiy, S. Menon, M. Qamar et al. Efficient parametrization of the atomic cluster expansion Physical Review Materials, 6, 013804, (2022)
S. Menon, Y. Lysogorskiy, J. Rogal, R. Drautz. Automated free-energy calculation from atomistic simulations Physical Review Materials, American Physical Society,, 5, 103801, (2021)
M. Rinaldi, M. Mrovec, M. Fähnle, R. Drautz. Determination of spin-wave stiffness in the Fe-Si system using first-principles calculations Physical Review B, 104, 064413, (2021)
