About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
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Symposium
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Materials Genome, CALPHAD, and a Career over the Span of 20, 50, and 60 Years: An FMD/SMD Symposium in Honor of Zi-Kui Liu
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Presentation Title |
Ab Initio Descriptors to Guide Materials Design in High-dimensional Chemical and Structural Configuration Spaces |
Author(s) |
Fritz Koermann, Tilmann Hickel, Joerg Neugebauer |
On-Site Speaker (Planned) |
Joerg Neugebauer |
Abstract Scope |
Modern engineering materials have evolved from simple single phase materials to nano-composites that employ dynamic mechanisms down to the atomistic scale. The structural and thermodynamic complexity of this new generation of structural materials presents severe challenges to their design. Ab initio approaches provide perfect tools to new design routes but face serious challenges when having to systematically sample high-dimensional chemical and structural configuration spaces. Combining advanced sampling, machine learning as well as thermodynamic concepts with our python based framework pyiron allows us in a highly automated way to combine first principles calculations with big data analytics and to obtain accurate ab initio descriptors. The flexibility and the power of these approaches will be demonstrated for compositionally complex alloys, where they allowed us to derive and employ new design concepts. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, High-Entropy Alloys, Modeling and Simulation |