Experimental Validation of Property Models and Databases for Computational Superalloy Design

• Published in: Advanced engineering materials Vol. 26; no. 16
• Main Authors: Gaag, Tobias, Weidinger, Julius, Bandorf, Jakob, Lux, Valeska, Wahlmann, Benjamin, Neumeier, Steffen, Zenk, Christopher, Körner, Carolin
• Format: Journal Article
• Language: English
• Published: 01.08.2024
• Subjects: CALPHAD; computational alloy developments; differential scanning calorimetry; optimizations; superalloys
• ISSN: 1438-1656; 1527-2648
• DOI: 10.1002/adem.202401051

Computational superalloy development is a powerful alternative to the conventional experimental approach. Based on thermodynamic databases and the CALPHAD method, it is possible to estimate the properties of a large number of potential alloys and select the most promising ones. However, the accuracy of the databases and complementary property models can be unsatisfying. The accuracy of two mass density and γ/γ′$\gamma / \left(\gamma\right)^{&aposx;}$ lattice parameter models and the TTNI8 and TCNI10 databases is analyzed in detail on the experimental basis of computationally optimized single‐crystalline superalloys. Various properties are measured and compared to the results of the property models and databases. Neither of the databases is superior to the other and especially the γ′$\left(\gamma\right)^{&aposx;}$ solvus temperature is not accurately described in both. The new mass density model, a linear regression based on the molar mass, is more reliable for low‐density alloys. Both lattice parameter model versions slightly overestimate the room‐temperature γ$$ \gamma $$ lattice parameter. The γ′$\left(\gamma\right)^{&aposx;}$ lattice parameter, however, is more accurately calculated using the new model version. The results of this study can be readily used to improve a multicriteria alloy optimization tool for computational superalloy design. The backbone of computational alloy design are thermodynamic databases for the CALPHAD method and property models. The accuracy of two databases and model versions for the mass density and the γ/γ′$\gamma / \left(\gamma\right)^{&aposx;}$ lattice misfit are evaluated. The experimental subject of this study are computationally optimized Ni‐based superalloys. This provides insight into the model and database performance in the unknown composition spaces.