Design and selection of high entropy alloys for hardmetal matrix applications using a coupled machine learning and CALPHAD methodology

This study aims to utilize a combined machine learning (ML) and CALculation of PHAse Diagrams (CALPHAD) methodology to design hardmetal matrix phases for metal-forming applications that can serve as the basis for carbide reinforcement. The vast compositional space that high entropy alloys (HEAs) occupy offers a promising avenue to satisfy the application design criteria of wear resistance and ductility. To efficiently explore this space, random forest ML models are constructed and trained from publicly available experimental HEA databases to make phase constitution and hardness predictions. Interrogation of the ML models constructed reveals accuracies >78.7% and a mean absolute error of 66.1 HV for phase and hardness predictions respectively. Six promising alloy compositions, extracted from the ML predictions and CALPHAD calculations, are experimentally fabricated and tested. The hardness predictions are found to be systematically under- and overpredicted depending on the alloy microstructure. In parallel, the phase classification models are found to lack sensitivity toward additional intermetallic phase formation. Despite the discrepancies identified between ML and experimental results, the fabricated compositions show promise for further experimental evaluation. These discrepancies are believed to be directly associated with the available databases but, importantly, have highlighted several avenues for both ML and database development

Effect of heat treatment on the microstructure, texture and elastic anisotropy of the nickel-based superalloy CM247LC processed by selective laser melting

Selective laser melting (SLM) of nickel-based superalloys is of great interest for the aerospace industry due to its capability for producing components with complex geometries. However, an improved understanding of the effect of SLM and subsequent post deposition heat treatments on the microstructure and mechanical properties is required to ensure that components with good structural integrity are produced. In this study, the microstructure, texture and elastic anisotropy of the nickel-based superalloy, CM247LC, in the as-SLM and heat-treated states have been analysed. The as-SLM microstructure showed fine elongated cells with a preferential alignment of along the build direction and a significant intercellular misorientation. Heat treatments at temperatures below 1230 °C resulted in a progressive recovery of the microstructure, whilst heat treatments above this temperature gave rise to a recrystallised microstructure. The extent to which nucleation and growth of the γ′ precipitates and secondary particles were affected by increasing the heat treatment temperature was also characterised. The bulk elastic anisotropy of all samples was measured by resonant ultrasound spectroscopy (RUS) and was found to be consistent with the local textures obtained by electron backscatter diffraction (EBSD). It was observed that the initially strong elastic anisotropy exhibited by the as-SLM material was significantly reduced in the recrystallised samples, although some anisotropy was retained as a result of their elongated grain microstructures