Advanced industries such as aerospace and medical technology rely on highly specialized metallic materials whose performance is driven by continuous and increasingly complex alloy development. To meet these demands, novel alloy concepts such as high-entropy alloys (HEAs) and advanced nickel-based alloys, often incorporating refractory elements, are becoming increasingly important.
The vast compositional design space and the high experimental effort required render purely empirical alloy development inefficient. In response, the research group pursues a simulation- and optimization-driven approach to systematically design new alloy systems.
To this end, the group develops multicriteria optimization software that combines deterministic and probabilistic models to identify optimal alloy compositions as Pareto fronts within a defined search space. The optimization framework is built upon CALPHAD-based thermodynamic and kinetic models, enabling the prediction of material properties and microstructural features with a strong physical foundation.
A central research focus is the prediction of mechanical properties directly from chemical composition, complemented by considerations of processability, particularly with respect to additive manufacturing. This integrated approach enables the targeted design of alloys tailored to complex geometries and advanced manufacturing technologies.
The developed methods are continuously advanced and experimentally validated within the framework of the Collaborative Research Center TR 103 “From Atoms to Single Crystals.” They contribute to accelerated, knowledge-based alloy development and facilitate the transfer of novel alloy concepts into industrial applications.
The vast compositional design space and the high experimental effort required render purely empirical alloy development inefficient. In response, the research group pursues a simulation- and optimization-driven approach to systematically design new alloy systems.
To this end, the group develops multicriteria optimization software that combines deterministic and probabilistic models to identify optimal alloy compositions as Pareto fronts within a defined search space. The optimization framework is built upon CALPHAD-based thermodynamic and kinetic models, enabling the prediction of material properties and microstructural features with a strong physical foundation.
A central research focus is the prediction of mechanical properties directly from chemical composition, complemented by considerations of processability, particularly with respect to additive manufacturing. This integrated approach enables the targeted design of alloys tailored to complex geometries and advanced manufacturing technologies.
The developed methods are continuously advanced and experimentally validated within the framework of the Collaborative Research Center TR 103 “From Atoms to Single Crystals.” They contribute to accelerated, knowledge-based alloy development and facilitate the transfer of novel alloy concepts into industrial applications.
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Publications:
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Design and Characterization of a Novel NiAl–(Cr,Mo) Eutectic Alloy
In: Advanced Engineering Materials (2024)
ISSN: 1438-1656
DOI: 10.1002/adem.202302079 - , , , , , , , :
Experimental Validation of Property Models and Databases for Computational Superalloy Design
In: Advanced Engineering Materials (2024)
ISSN: 1438-1656
DOI: 10.1002/adem.202401051 - , , , , , , :
Accelerating Alloy Development for Additive Manufacturing
15th International Symposium on Superalloys, ISS 2024 (Pennsylvania, PA, 8. September 2024 - 12. September 2024)
In: Jonathan Cormier, Ian Edmonds, Stephane Forsik, Paraskevas Kontis, Corey O’Connell, Timothy Smith, Akane Suzuki, Sammy Tin, Jian Zhang (ed.): Minerals, Metals and Materials Series 2024
DOI: 10.1007/978-3-031-63937-1_11 - :
Numerische Entwicklung von Superlegierungen für den Guss und die Additive Fertigung (Dissertation, 2024) - , , , , , , , , , :
Numerical Design of CoNi-Base Superalloys With Improved Casting Structure
In: Metallurgical and Materials Transactions A-Physical Metallurgy and Materials Science (2022)
ISSN: 1073-5623
DOI: 10.1007/s11661-022-06870-4 - , , , :
Numerical Alloy Development for Additive Manufacturing towards Reduced Cracking Susceptibility
In: Crystals 11 (2021)
ISSN: 2073-4352
DOI: 10.3390/cryst11080902 - , , , , , , :
MultOpt++: a fast regression-based model for the constraint violation fraction due to composition uncertainties
In: Modelling and Simulation in Materials Science and Engineering 27 (2019)
ISSN: 0965-0393
DOI: 10.1088/1361-651X/aaf01e - , , , , , , , :
MultOpt++: a fast regression-based model for the development of compositions with high robustness against scatter of element concentrations
In: Modelling and Simulation in Materials Science and Engineering 27 (2019)
ISSN: 0965-0393
DOI: 10.1088/1361-651X/aaf0b8 - , , , , , , , , , , , , , , , , :
Development of Single-Crystal Ni-Base Superalloys Based on Multi-criteria Numerical Optimization and Efficient Use of Refractory Elements
In: Metallurgical and Materials Transactions A-Physical Metallurgy and Materials Science 49A (2018), p. 4134-4145
ISSN: 1073-5623
DOI: 10.1007/s11661-018-4759-0 - , , , , , :
Development of a low-density rhenium-free single crystal nickel-based superalloy by application of numerical multi-criteria optimization using thermodynamic calculations
13th International Symposium on Superalloys, SUPERALLOYS 2016 (Seven Springs, 11. September 2016 - 15. September 2016)
In: M. Hardy, E. Huron, U. Glatzel, B. Griffin, B. Lewis, C. Rae, V. Seetharaman, S. Tin (ed.): Superalloys 2016: Proceedings of the 13th Intenational Symposium of Superalloys 2016
DOI: 10.1002/9781119075646.ch4