Automated high-throughput data collection and analysis of composition-process-structure relations by utilizing casting segregation in a Ni-base superalloy

Thomas Hoefler; Ayako Ikeda; Satoshi Utada; Makoto Osawa; Kyoko Kawagishi; Toru Hara; Takahito Ohmura; Daichi Akama; Masaki Taneike; Toshio Osada

doi:10.1016/j.matdes.2026.116820

ジャーナル論文 Automated high-throughput data collection and analysis of composition-process-structure relations by utilizing casting segregation in a Ni-base superalloy

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Thomas Hoefler, Ayako Ikeda, Satoshi Utada, Makoto Osawa, Kyoko Kawagishi, Toru Hara, Takahito Ohmura, Daichi Akama, Masaki Taneike, Toshio Osada. Automated high-throughput data collection and analysis of composition-process-structure relations by utilizing casting segregation in a Ni-base superalloy. MATERIALS & DESIGN. 2026, 270 (), 116820. https://doi.org/10.1016/j.matdes.2026.116820

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(abstract)

We attempt to address the problem of generating large, reliable experimental datasets that interrelate composition, processing and microstructure in a short timeframe by combining a heterogeneously composed sample with a gradient heat treatment. Composition-Process-Structure datasets are essential for both physical and purely statistical models aiming to predict material behavior. Using the segregated microstructure of a cast single-crystal sample of gas turbine blade Ni-base superalloy MGA1400 in combination with a temperature gradient furnace, we cover a whole range of heat treatment temperatures and compositions according to elemental partitioning. Data collection uses automatic, correlative FE-SEM and EPMA analysis for microstructure images with corresponding local concentration. Image analysis combined with a precipitate shape fitting method using superellipses allows automatic evaluation of phase fractions, precipitate size/shape/aspect distributions as well as inter-precipitate distances and relative angles for investigating clustering and alignment phenomena. As a result, we were able to generate a pseudobinary phase diagram indicating the γ′solvus. The activation energy for coarsening of γ′was found to be mostly independent of as-segregated composition. Further, results showed lattice misfit between the γ and γ′phase to not only cause precipitate shape to vary with treatment temperature, but also cause precipitate aspect ratio to vary between the dendrite core and interdendrite regions, indicating the presence of dendritic stresses from solidification.

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