Abstract

Multi-principal element alloys (MPEAs) have been the focus of study and computationally-guided design for two reasons. MPEAs have shown high strengths and, the vast potential compositional space is more efficiently navigated with machine learning. In this article, we present data from 7385 indentation tests performed on 19 different MPEAs. Samples were arc melted, a thermodynamically complex process forming many distinct phases within a sample. The database was generated by performing hundreds of nanoindentation tests on a given sample and registering the location of those indents with local phase compositions measured with energy dispersive spectroscopy (EDS). The database contains the phases formed in the MPEA, the composition at the location of each indent, and the associated hardness (HV) and modulus for each indent. This data allows researchers targeting data-driven design of high strength systems to extract meaningful correlations between alloying composition, the resulting phases, and mechanical properties for future study.

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