Dataset for machine learning of microstructures for 9% Cr steels

The microstructure of steel greatly influences the mechanical properties. For 9 wt% Cr steels, which are widely used in the power generation industry, the steels have a ferritic and martensitic microstructure which can be altered by heat treating and chemical composition variations. Fully martensitic steels typically having high yield strengths but low ductility. Tempering can reduce the amount of martensite in the steel lowering the yield strength but increasing the ductility of the alloy. Alloying can alter the time required for a martensitic transformation. In authors' previously published research, the authors used machine learning methodology to predict room temperature tensile properties from scanning electron microscopy (SEM) images of the initial steel microstructures from a wide range of steel compositions. This data-in-brief supplies the raw image files and the associated tensile properties for the authors' previously published research utilized to predict tensile properties of steels [1].