Lattice Misfit Predictions via the Gaussian Process Regression for Ni-Based Single Crystal Superalloys

Ni-based single crystal superalloys exhibit superb mechanical strength, particularly, creep resistance at elevated temperature. The unique microstructure, which is consisted of gamma and gamma' phases, is a major factor that determines the mechanical behavior of these alloys. The lattice misfit between the two phases is of particular interest in understanding and predicting the deformation mechanism. The measurement of the lattice misfit by advanced analytical instruments is costly and difficult. In current study, we develop the Gaussian process regression model to predict lattice misfits for Ni-based single crystal superalloys based on chemical composition, temperature, and two morphological indicators. The model is highly stable and accurate and promising as a fast, robust, and low-cost tool for lattice misfit estimations.

Automated summary

This study focuses on the unique microstructure of Ni-based single crystal superalloys and the lattice misfit between gamma and gamma' phases. By developing a Gaussian process regression model, the researchers are able to predict lattice misfits based on chemical composition, temperature, and two morphological indicators. This model is highly stable, accurate, and promising for fast, robust, and low-cost lattice misfit estimations.