Consistent Quantification of Precipitate Shapes and Sizes in Two and Three Dimensions Using Central Moments

Computational microstructure design aims to fully exploit the precipitate strengthening potential of an alloy system. The development of accurate models to describe the temporal evolution of precipitate shapes and sizes is of great technological relevance. The experimental investigation of the precipitate microstructure is mostly based on two-dimensional micrographic images. Quantitative modeling of the temporal evolution of these microstructures needs to be discussed in three-dimensional simulation setups. To consistently bridge the gap between 2D images and 3D simulation data, we employ the method of central moments. Based on this, the aspect ratio of plate-like particles is consistently defined in two and three dimensions. The accuracy and interoperability of the method is demonstrated through representative 2D and 3D pixel-based sample data containing particles with a predefined aspect ratio. The applicability of the presented approach in integrated computational materials engineering (ICME) is demonstrated by the example of gamma '' microstructure coarsening in Ni-based superalloys at 730 degrees C. For the first time, gamma '' precipitate shape information from experimental 2D images and 3D phase-field simulation data is directly compared. This coarsening data indicates deviations from the classical ripening behavior and reveals periods of increased precipitate coagulation.

Automated summary

Computational microstructure design aims to fully utilize the potential strengthening effect of precipitates in alloy systems. Accurate models for describing the temporal evolution of precipitate shapes and sizes are important for technological development. This study proposes the use of central moments to bridge the gap between 2D images and 3D simulations. The method demonstrates its accuracy and interoperability through the analysis of representative samples with predefined aspect ratios.