Dataset for machine learning guided prediction of the yield strength and hardness of multi-principal element alloys

This effort was principally supported by the U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy (EERE) under the Advanced Manufacturing Office (Project WBS 2.1.0.19) through Ames Laboratory, which is operated for the U.S. DOE by Iowa State University under contract DE-AC02-07CH11358.

These data sets were used to develop machine-learning models to predict yield strength and hardness of multi-principal element alloys. We mainly collected the alloys and their mechanical properties from different published works. A list of references is provided at the end of each data set.

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